reworking SP logic into composed handler

.github/workflows/base.yml

@@ -52,12 +52,6 @@ jobs:
             python_version: "3.11"
             pytorch: nightly
             torch_cuda_arch_list: "7.0 7.5 8.0 8.6 8.7 8.9 9.0+PTX"
-          - cuda: "128"
-            cuda_version: 12.8.1
-            cudnn_version: ""
-            python_version: "3.11"
-            pytorch: next
-            torch_cuda_arch_list: "7.0 7.5 8.0 8.6 8.7 8.9 9.0+PTX"
     steps:
       - name: Checkout
         uses: actions/checkout@v4
@@ -79,7 +73,7 @@ jobs:
         uses: docker/build-push-action@v4
         with:
           context: .
-          file: ${{ matrix.pytorch == 'nightly' && './docker/Dockerfile-base-nightly' || matrix.pytorch == 'next' && './docker/Dockerfile-base-next' || './docker/Dockerfile-base' }}
+          file: ${{ matrix.pytorch == 'nightly' && './docker/Dockerfile-base-nightly' || './docker/Dockerfile-base' }}
           push: ${{ github.event_name != 'pull_request' }}
           tags: ${{ steps.metadata.outputs.tags }}-base-py${{ matrix.python_version }}-cu${{ matrix.cuda }}-${{ matrix.pytorch }}${{ matrix.axolotl_extras != '' && '-' || '' }}${{ matrix.axolotl_extras }}
           labels: ${{ steps.metadata.outputs.labels }}

cicd/multigpu.sh

@@ -2,5 +2,5 @@
 set -e
 
 # only run one test at a time so as not to OOM the GPU
-pytest -v  --durations=10 -n2 /workspace/axolotl/tests/e2e/multigpu/ --ignore=/workspace/axolotl/tests/e2e/multigpu/solo/
-pytest -v  --durations=10 -n1 /workspace/axolotl/tests/e2e/multigpu/solo/
+pytest -v -n2 /workspace/axolotl/tests/e2e/multigpu/ --ignore=/workspace/axolotl/tests/e2e/multigpu/solo/
+pytest -v -n1 /workspace/axolotl/tests/e2e/multigpu/solo/

docker/Dockerfile

@@ -20,9 +20,9 @@ WORKDIR /workspace/axolotl
 
 # If AXOLOTL_EXTRAS is set, append it in brackets
 RUN if [ "$AXOLOTL_EXTRAS" != "" ] ; then \
-        pip install --no-build-isolation -e .[deepspeed,flash-attn,ring-flash-attn,optimizers,ray,$AXOLOTL_EXTRAS] $AXOLOTL_ARGS; \
+        pip install --no-build-isolation -e .[deepspeed,flash-attn,optimizers,ray,$AXOLOTL_EXTRAS] $AXOLOTL_ARGS; \
     else \
-        pip install --no-build-isolation -e .[deepspeed,flash-attn,ring-flash-attn,optimizers,ray] $AXOLOTL_ARGS; \
+        pip install --no-build-isolation -e .[deepspeed,flash-attn,optimizers,ray] $AXOLOTL_ARGS; \
     fi
 
 RUN python scripts/unsloth_install.py | sh

docker/Dockerfile-base-next

@@ -1,38 +0,0 @@
-ARG CUDA_VERSION="12.8.1"
-ARG CUDNN_VERSION="8"
-ARG UBUNTU_VERSION="22.04"
-ARG MAX_JOBS=4
-
-FROM nvidia/cuda:$CUDA_VERSION-cudnn$CUDNN_VERSION-devel-ubuntu$UBUNTU_VERSION AS base-builder
-
-ENV PATH="/root/miniconda3/bin:${PATH}"
-
-ARG PYTHON_VERSION="3.11"
-ARG PYTORCH_VERSION="next"
-ARG CUDA="128"
-ARG TORCH_CUDA_ARCH_LIST="7.0 7.5 8.0 8.6 9.0+PTX"
-
-ENV PYTHON_VERSION=$PYTHON_VERSION
-ENV TORCH_CUDA_ARCH_LIST=$TORCH_CUDA_ARCH_LIST
-
-RUN apt-get update \
-    && apt-get install -y wget git build-essential ninja-build git-lfs libaio-dev pkg-config && rm -rf /var/lib/apt/lists/* \
-    && wget \
-    https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh \
-    && mkdir /root/.conda \
-    && bash Miniconda3-latest-Linux-x86_64.sh -b \
-    && rm -f Miniconda3-latest-Linux-x86_64.sh \
-    && conda create -n "py${PYTHON_VERSION}" python="${PYTHON_VERSION}"
-
-ENV PATH="/root/miniconda3/envs/py${PYTHON_VERSION}/bin:${PATH}"
-
-WORKDIR /workspace
-
-RUN python3 -m pip install --upgrade pip && pip3 install packaging && \
-    python3 -m pip install --no-cache-dir -U torch==2.7.0 --extra-index-url https://download.pytorch.org/whl/test/cu$CUDA && \
-    python3 -m pip install --no-cache-dir "causal_conv1d @ git+https://github.com/Dao-AILab/causal-conv1d.git@main" && \
-    python3 -m pip install --no-cache-dir "mamba_ssm @ git+https://github.com/state-spaces/mamba.git@main"
-
-RUN git lfs install --skip-repo && \
-    pip3 install awscli && \
-    pip3 install -U --no-cache-dir pydantic==2.10.6

docs/config.qmd

@@ -510,8 +510,7 @@ train_on_inputs: false
 # Note that training loss may have an oscillating pattern with this enabled.
 group_by_length: false
 
-# Whether to use gradient checkpointing. Available options are: true, false, "offload".
-# https://huggingface.co/docs/transformers/v4.18.0/en/performance#gradient-checkpointing
+# Whether to use gradient checkpointing https://huggingface.co/docs/transformers/v4.18.0/en/performance#gradient-checkpointing
 gradient_checkpointing: false
 # additional kwargs to pass to the trainer for gradient checkpointing
 # gradient_checkpointing_kwargs:
@@ -687,9 +686,10 @@ ddp_broadcast_buffers:
 # E.g., if 4 GPUs are available, set this value to 2 to split each sequence into two equal-sized
 # subsequences, or set to 4 to split into four equal-sized subsequences.
 # See https://axolotl-ai-cloud.github.io/axolotl/docs/sequence_parallelism.html for more details.
-sequence_parallel_degree:
-# Optional; strides across the key dimension. Larger values use more memory but should make training faster.
-# Must evenly divide the number of KV heads in your model.
+sequence_parallel_degree: 4  # Set to the number of GPUs to split sequences across
+flash_attention: true  # SP requires flash attention
+micro_batch_size: 1  # SP requires this is set to 1
+# (optional) strides across the key dimension; larger values use more memory but should make training a bit faster
 heads_k_stride: 1
 
 # Path to torch distx for optim 'adamw_anyprecision'

docs/lora_optims.qmd

@@ -17,7 +17,6 @@ We currently support several common model architectures, including (but not limi
 - `qwen2`
 - `gemma`
 - `gemma2`
-- `gemma3`
 
 <details>
 

docs/sequence_parallelism.qmd

@@ -23,9 +23,10 @@ Use sequence parallelism when:
 To enable sequence parallelism, add the following to your configuration file:
 
 ```yaml
-# Set to a divisor (> 1) of the number of GPUs available
-sequence_parallel_degree: 4  # Split sequences across 4 GPUs
-# Optional; strides across the key dimension. Larger values use more memory but should make training faster.
+sequence_parallel_degree: 4  # Split each sequence into 4 parts, one per GPU
+flash_attention: true  # SP requires flash attention
+micro_batch_size: 1  # SP requires this is set to 1
+# (optional) strides across the key dimension; larger values use more memory but should make training a bit faster
 heads_k_stride: 1
 ```
 
@@ -66,15 +67,16 @@ sequence_len: 8192
 ...
 
 sequence_parallel_degree: 4  # Split each sequence into 4 parts, one per GPU
-flash_attention: true  # Required with sequence parallelism
-# Optional; strides across the key dimension. Larger values use more memory but should make training faster.
+flash_attention: true  # SP requires flash attention
+micro_batch_size: 1  # SP requires this is set to 1
+# (optional) strides across the key dimension; larger values use more memory but should make training a bit faster
 heads_k_stride: 1
 
 ...
 ```
 
-This will train the Llama 3 8B model with 8K context length, with each sequence split
-into 2 subsequences of length 4096 across 2 GPUs.
+This will train the Llama 3 8B model with 8192 context length, with each sequence split
+into 4 subsequences of length 2048 across 4 GPUs.
 
 ## Sample Packing with Sequence Parallelism
 
@@ -86,12 +88,14 @@ Sequence parallelism is compatible with Axolotl's sample packing functionality.
 
 ## Effect on Batch Size
 
+First, note that sequence parallelism supports only the case where `micro_batch_size: 1`.
+
 When using sequence parallelism, your effective global batch size is **divided** by the `sequence_parallel_degree`. This happens because:
 
 - Each group of `sequence_parallel_degree` GPUs works on the same batch (just different parts of each sequence)
 - The number of batches processed per step decreases
 
 For example:
-- With 8 GPUs and no sequence parallelism: 8 different batches processed per step
+- With 8 GPUs and no sequence parallelism: 8 different batches are processed per step
 - With 8 GPUs and `sequence_parallel_degree=4`: Only 2 different batches processed per step (each split across 4 GPUs)
-- If your per-GPU `micro_batch_size` is 2, the global batch size decreases from 16 to 4
+- If your per-GPU `micro_batch_size` is 1, the global batch size decreases from 8 to 2

examples/cerebras/btlm-ft.yml

@@ -8,6 +8,9 @@ tokenizer_type: GPT2Tokenizer
 trust_remote_code: true
 tokenizer_use_fast: true
 tokenizer_legacy: true
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 push_dataset_to_hub:
 hf_use_auth_token: true
@@ -31,6 +34,7 @@ lora_alpha:
 lora_dropout:
 lora_target_modules:
 lora_target_linear:
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -54,12 +58,16 @@ learning_rate: 0.000085
 train_on_inputs: true
 group_by_length: false
 bf16: auto
+fp16:
 tf32: true
 
 gradient_checkpointing: false
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
 
+xformers_attention:
 flash_attention: true
 sdp_attention:
 flash_optimum:
@@ -72,6 +80,8 @@ evals_per_epoch: 4
 saves_per_epoch: 1
 save_total_limit:
 
+debug:
+deepspeed:
 weight_decay: 0.1
 special_tokens:
   pad_token: "<|endoftext|>"

examples/cerebras/qlora.yml

@@ -22,6 +22,7 @@ lora_target_modules:
   - c_attn
   - c_proj
 lora_target_linear:
+lora_fan_in_fan_out:
 wandb_project:
 wandb_entity:
 wandb_watch:
@@ -35,10 +36,15 @@ optimizer: paged_adamw_8bit
 torchdistx_path:
 lr_scheduler: cosine
 learning_rate: 0.0002
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: true
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
 xformers_attention: true
 flash_attention:
@@ -47,6 +53,10 @@ gptq_model_v1:
 warmup_steps: 10
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.1
+fsdp:
+fsdp_config:
 special_tokens:
   pad_token: "<|endoftext|>"

examples/code-llama/13b/lora.yml

@@ -26,6 +26,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -40,18 +41,29 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
+s2_attention:
 
 warmup_steps: 10
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
   bos_token: "<s>"
   eos_token: "</s>"

examples/code-llama/13b/qlora.yml

@@ -26,7 +26,9 @@ pad_to_sequence_len: true
 lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
+lora_target_modules:
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -41,18 +43,28 @@ optimizer: paged_adamw_32bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 10
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
   bos_token: "<s>"
   eos_token: "</s>"

examples/code-llama/34b/lora.yml

@@ -26,6 +26,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -40,18 +41,29 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
+s2_attention:
 
 warmup_steps: 10
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
   bos_token: "<s>"
   eos_token: "</s>"

examples/code-llama/34b/qlora.yml

@@ -26,7 +26,9 @@ pad_to_sequence_len: true
 lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
+lora_target_modules:
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -41,18 +43,28 @@ optimizer: paged_adamw_32bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 10
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
   bos_token: "<s>"
   eos_token: "</s>"

examples/code-llama/7b/lora.yml

@@ -26,6 +26,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -40,18 +41,29 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
+s2_attention:
 
 warmup_steps: 10
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
   bos_token: "<s>"
   eos_token: "</s>"

examples/code-llama/7b/qlora.yml

@@ -26,7 +26,9 @@ pad_to_sequence_len: true
 lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
+lora_target_modules:
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -41,18 +43,28 @@ optimizer: paged_adamw_32bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 10
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
   bos_token: "<s>"
   eos_token: "</s>"

examples/cohere/command-r-7b-qlora.yml

@@ -44,16 +44,28 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: true
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_ratio: 0.1
 evals_per_epoch:
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:

examples/dbrx/16bit-lora.yaml

@@ -3,6 +3,9 @@ base_model: LnL-AI/dbrx-base-converted-v2
 # hub_model_id: username/custom_model_name
 
 trust_remote_code: true
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 datasets:
@@ -45,20 +48,26 @@ optimizer: paged_adamw_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: false  # don't use with fsdp_activation_checkpointing
 gradient_checkpointing_kwargs:
   use_reentrant: false
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 10
 evals_per_epoch:
 saves_per_epoch: 1
-
+debug:
 weight_decay: 0.0
 fsdp:
   - full_shard

examples/dbrx/8bit-lora.yaml

@@ -48,20 +48,26 @@ optimizer: paged_adamw_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: false  # don't use with fsdp_activation_checkpointing
 gradient_checkpointing_kwargs:
   use_reentrant: false
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 10
 evals_per_epoch:
 saves_per_epoch: 1
-
+debug:
 weight_decay: 0.0
 fsdp:
   - full_shard

examples/dbrx/fft-ds-zero3.yaml

@@ -3,6 +3,9 @@ base_model: LnL-AI/dbrx-base-converted-v2
 # hub_model_id: username/custom_model_name
 
 trust_remote_code: true
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 datasets:
@@ -32,19 +35,25 @@ optimizer: paged_adamw_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
 gradient_checkpointing_kwargs:
   use_reentrant: false
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 10
 evals_per_epoch:
 saves_per_epoch: 1
-
+debug:
 weight_decay: 0.0
 deepspeed: deepspeed_configs/zero3_bf16.json

examples/deepseek-v2/fft-fsdp-16b.yaml

@@ -2,6 +2,9 @@ base_model: deepseek-ai/DeepSeek-V2-Lite
 # Automatically upload checkpoint and final model to HF
 # hub_model_id: username/custom_model_name
 trust_remote_code: true
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 datasets:
@@ -28,19 +31,27 @@ optimizer: adamw_torch_fused
 lr_scheduler: cosine
 learning_rate: 2e-5
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
 gradient_checkpointing_kwargs:
   use_reentrant: false
+early_stopping_patience:
 resume_from_checkpoint:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 100
 evals_per_epoch: 2
+eval_table_size:
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
 special_tokens:
 fsdp:

examples/deepseek-v2/qlora-fsdp-2_5.yaml

@@ -52,19 +52,27 @@ optimizer: adamw_torch_fused
 lr_scheduler: cosine
 learning_rate: 2e-5
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
 gradient_checkpointing_kwargs:
   use_reentrant: false
+early_stopping_patience:
 resume_from_checkpoint:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 100
 evals_per_epoch: 2
+eval_table_size:
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
 special_tokens:
 fsdp:

examples/falcon/config-7b-lora.yml

@@ -25,7 +25,9 @@ max_packed_sequence_len:
 lora_r: 16
 lora_alpha: 32
 lora_dropout: 0.0
+lora_target_modules:
 lora_target_linear: true
+lora_fan_in_fan_out:
 wandb_project:
 wandb_entity:
 wandb_watch:
@@ -39,10 +41,15 @@ optimizer: adamw_bnb_8bit
 torchdistx_path:
 lr_scheduler: cosine
 learning_rate: 0.00003
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: true
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
 xformers_attention: true
 flash_attention:
@@ -51,7 +58,11 @@ gptq_model_v1:
 warmup_steps: 40
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
   pad_token: "<|endoftext|>"
   bos_token: "<|endoftext|>"

examples/falcon/config-7b-qlora.yml

@@ -38,7 +38,9 @@ lora_alpha: 16
 # 0.05 for 33B and 65B models
 lora_dropout: 0.05
 # add LoRA modules on all linear layers of the base model
+lora_target_modules:
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -65,7 +67,10 @@ lr_scheduler: cosine
 # - 2e-4 for 7b & 13b
 # - 1e-4 for 33b & 64b
 learning_rate: 0.0002
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: true
 gradient_checkpointing: true
 # stop training after this many evaluation losses have increased in a row
@@ -73,6 +78,7 @@ gradient_checkpointing: true
 early_stopping_patience: 3
 resume_from_checkpoint:
 auto_resume_from_checkpoints: true
+local_rank:
 logging_steps: 1
 xformers_attention: true
 flash_attention:
@@ -81,7 +87,11 @@ gptq_model_v1:
 warmup_steps: 10
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.000001
+fsdp:
+fsdp_config:
 special_tokens:
   pad_token: "<|endoftext|>"
   bos_token: "<|endoftext|>"

examples/falcon/config-7b.yml

@@ -7,6 +7,9 @@ tokenizer_type: AutoTokenizer
 
 # required by falcon custom model code: https://huggingface.co/tiiuae/falcon-7b/tree/main
 trust_remote_code: true
+
+load_in_8bit: false
+load_in_4bit: false
 gptq: false
 strict: false
 push_dataset_to_hub:
@@ -22,7 +25,9 @@ max_packed_sequence_len:
 lora_r: 64
 lora_alpha: 32
 lora_dropout: 0.0
+lora_target_modules:
 lora_target_linear: true
+lora_fan_in_fan_out:
 wandb_project:
 wandb_entity:
 wandb_watch:
@@ -36,10 +41,15 @@ optimizer: adamw_bnb_8bit
 torchdistx_path:
 lr_scheduler: cosine
 learning_rate: 0.00003
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: true
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
 xformers_attention: true
 flash_attention:
@@ -48,7 +58,11 @@ gptq_model_v1:
 warmup_steps: 40
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
   pad_token: "<|endoftext|>"
   bos_token: "<|endoftext|>"

examples/gemma/qlora.yml

@@ -42,16 +42,28 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_ratio: 0.1
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:

examples/gemma2/qlora.yml

@@ -48,16 +48,28 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: true
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_ratio: 0.1
 evals_per_epoch:
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:

examples/gemma2/reward-model.yaml

@@ -5,6 +5,9 @@ num_labels: 1
 tokenizer_type: AutoTokenizer
 # Automatically upload checkpoint and final model to HF
 # hub_model_id: username/custom_model_name
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 reward_model: true
@@ -35,6 +38,8 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: true
 fp16:
 tf32: true
@@ -42,12 +47,21 @@ tf32: true
 gradient_checkpointing: true
 gradient_checkpointing_kwargs:
   use_reentrant: false
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_ratio: 0.1
 evals_per_epoch:
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:

examples/gemma3/gemma-3-1b-qlora.yml

@@ -50,18 +50,30 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: true
 
 gradient_checkpointing: true
 gradient_checkpointing_kwargs:
   use_reentrant: false
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_ratio: 0.1
 evals_per_epoch:
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:

examples/gemma3/gemma-3-4b-lora.yml

@@ -2,8 +2,6 @@ base_model: google/gemma-3-4b-it
 processor_type: AutoProcessor
 strict: false
 
-load_in_4bit: true
-
 # these 3 lines are needed for now to handle vision chat templates w images
 skip_prepare_dataset: true
 remove_unused_columns: false
@@ -22,7 +20,7 @@ dataset_prepared_path: last_run_prepared
 val_set_size: 0.01
 output_dir: ./outputs/out
 
-adapter: qlora
+adapter: lora
 lora_model_dir:
 
 sequence_len: 2048
@@ -46,6 +44,8 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: true
 fp16:
 tf32: true
@@ -53,6 +53,7 @@ tf32: true
 gradient_checkpointing: true
 gradient_checkpointing_kwargs:
   use_reentrant: false
+local_rank:
 logging_steps: 1
 flash_attention: true
 eager_attention:
@@ -60,4 +61,8 @@ eager_attention:
 warmup_ratio: 0.1
 evals_per_epoch: 1
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:

examples/gemma3/gemma-3-4b-qlora.yml

@@ -1,61 +0,0 @@
-base_model: google/gemma-3-4b-it
-strict: false
-
-load_in_4bit: true
-
-# gemma3 doesn't seem to play nice with ddp
-ddp_find_unused_parameters: true
-
-chat_template: gemma3
-datasets:
-  - path: cgato/SlimOrcaDedupCleaned
-    type: chat_template
-    field_messages: conversations
-    message_property_mappings:
-      role: from
-      content: value
-
-dataset_prepared_path: last_run_prepared
-val_set_size: 0.01
-output_dir: ./outputs/out
-
-adapter: qlora
-lora_model_dir:
-
-sequence_len: 2048
-sample_packing: true
-pad_to_sequence_len: true
-
-lora_r: 32
-lora_alpha: 16
-lora_dropout: 0.05
-lora_target_modules: 'language_model.model.layers.[\d]+.(mlp|cross_attn|self_attn).(up|down|gate|q|k|v|o)_proj'
-
-wandb_project:
-wandb_entity:
-wandb_watch:
-wandb_name:
-wandb_log_model:
-
-gradient_accumulation_steps: 4
-micro_batch_size: 2
-num_epochs: 1
-optimizer: adamw_bnb_8bit
-lr_scheduler: cosine
-learning_rate: 0.0002
-
-bf16: true
-fp16:
-tf32: true
-
-gradient_checkpointing: true
-gradient_checkpointing_kwargs:
-  use_reentrant: false
-logging_steps: 1
-flash_attention: true
-eager_attention:
-
-warmup_ratio: 0.1
-evals_per_epoch: 1
-saves_per_epoch: 1
-weight_decay: 0.0

examples/gptj/qlora.yml

@@ -18,7 +18,9 @@ max_packed_sequence_len:
 lora_r: 8
 lora_alpha: 32
 lora_dropout: 0.05
+lora_target_modules:
 lora_target_linear: true
+lora_fan_in_fan_out:
 wandb_project:
 wandb_entity:
 wandb_watch:
@@ -32,10 +34,15 @@ optimizer: paged_adamw_8bit
 torchdistx_path:
 lr_scheduler: cosine
 learning_rate: 0.0001
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: true
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
 xformers_attention: true
 flash_attention:
@@ -44,6 +51,10 @@ gptq_model_v1:
 warmup_steps: 10
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.1
+fsdp:
+fsdp_config:
 special_tokens:
   pad_token: "<|endoftext|>"

examples/jamba/qlora.yaml

@@ -40,18 +40,26 @@ optimizer: paged_adamw_8bit
 lr_scheduler: cosine
 learning_rate: 0.00001
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
 gradient_checkpointing_kwargs:
   use_reentrant: false
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 10
 evals_per_epoch:
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
 special_tokens:

examples/jamba/qlora_deepspeed.yaml

@@ -39,20 +39,26 @@ optimizer: paged_adamw_8bit
 lr_scheduler: cosine
 learning_rate: 0.00001
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
 gradient_checkpointing_kwargs:
   use_reentrant: false
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 10
 evals_per_epoch:
 saves_per_epoch: 1
-
+debug:
 deepspeed: deepspeed_configs/zero2.json
 weight_decay: 0.0
 special_tokens:

examples/jamba/qlora_fsdp_large.yaml

@@ -39,6 +39,8 @@ optimizer: adamw_torch_fused
 lr_scheduler: cosine
 learning_rate: 0.00001
 
+train_on_inputs: false
+group_by_length: false
 bf16: true
 tf32: true
 

examples/jeopardy-bot/config.yml

@@ -33,9 +33,13 @@ optimizer: adamw_bnb_8bit
 torchdistx_path:
 lr_scheduler: cosine
 learning_rate: 0.00003
+train_on_inputs: false
+group_by_length: false
 bf16: auto
 tf32: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 5
 xformers_attention: true
 flash_attention:
@@ -44,7 +48,11 @@ gptq_model_v1:
 warmup_steps: 20
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.1
+fsdp:
+fsdp_config:
 tokens:
   bos_token: "<s>"
   eos_token: "</s>"

examples/llama-2/fft_optimized.yml

@@ -4,6 +4,9 @@ model_type: LlamaForCausalLM
 tokenizer_type: LlamaTokenizer
 # Automatically upload checkpoint and final model to HF
 # hub_model_id: username/custom_model_name
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 datasets:
@@ -23,6 +26,7 @@ lora_r:
 lora_alpha:
 lora_dropout:
 lora_target_linear:
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -37,12 +41,18 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 flash_attn_cross_entropy: false
 flash_attn_rms_norm: true
@@ -51,8 +61,11 @@ flash_attn_fuse_mlp: true
 
 warmup_steps: 100
 evals_per_epoch: 4
+eval_table_size:
 saves_per_epoch: 1
-
+debug:
 deepspeed: #deepspeed_configs/zero2.json # multi-gpu only
 weight_decay: 0.1
+fsdp:
+fsdp_config:
 special_tokens:

examples/llama-2/gptq-lora.yml

@@ -10,6 +10,8 @@ gptq_disable_exllama: true
 
 tokenizer_use_fast: true
 tokenizer_legacy: true
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 push_dataset_to_hub:
 hf_use_auth_token: true
@@ -31,6 +33,7 @@ lora_target_modules:
   - q_proj
   - v_proj
 lora_target_linear:
+lora_fan_in_fan_out:
 wandb_project:
 wandb_watch:
 wandb_name:
@@ -47,19 +50,26 @@ torchdistx_path:
 lr_scheduler: cosine
 lr_quadratic_warmup: true
 learning_rate: 0.000017
+train_on_inputs: false
+group_by_length: false
 bf16: false
 fp16: false
 float16: true
 tf32: true
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention:
 sdp_attention:
 flash_optimum:
 warmup_steps: 100
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.1
 special_tokens:
   bos_token: "<s>"

examples/llama-2/lisa.yml

@@ -4,6 +4,9 @@ model_type: LlamaForCausalLM
 tokenizer_type: LlamaTokenizer
 # Automatically upload checkpoint and final model to HF
 # hub_model_id: username/custom_model_name
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 datasets:
@@ -23,6 +26,7 @@ lora_r:
 lora_alpha:
 lora_dropout:
 lora_target_linear:
+lora_fan_in_fan_out:
 
 lisa_n_layers: 4
 lisa_step_interval: 20
@@ -41,12 +45,18 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 5e-5 # recommendation from lisa paper for 7b
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 flash_attn_cross_entropy: false
 flash_attn_rms_norm: true
@@ -55,8 +65,13 @@ flash_attn_fuse_mlp: true
 
 warmup_steps: 100
 evals_per_epoch: 4
+eval_table_size:
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.1
+fsdp:
+fsdp_config:
 special_tokens:
   bos_token: "<s>"
   eos_token: "</s>"

examples/llama-2/loftq.yml

@@ -4,6 +4,9 @@ model_type: LlamaForCausalLM
 tokenizer_type: LlamaTokenizer
 # Automatically upload checkpoint and final model to HF
 # hub_model_id: username/custom_model_name
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 datasets:
@@ -23,6 +26,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 peft:
   loftq_config:
     loftq_bits: 4
@@ -40,16 +44,29 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
+s2_attention:
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:

examples/llama-2/lora.yml

@@ -26,6 +26,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -40,16 +41,29 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
+s2_attention:
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:

examples/llama-2/qlora-fsdp.yml

@@ -26,7 +26,9 @@ pad_to_sequence_len: true
 lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
+lora_target_modules:
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -41,19 +43,28 @@ optimizer: adamw_torch_fused
 lr_scheduler: cosine
 learning_rate: 0.00001
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
 gradient_checkpointing_kwargs:
   use_reentrant: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
 fsdp:
   - full_shard

examples/llama-2/qlora.yml

@@ -26,7 +26,9 @@ pad_to_sequence_len: true
 lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
+lora_target_modules:
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -41,16 +43,27 @@ optimizer: paged_adamw_32bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:

examples/llama-2/relora.yml

@@ -24,7 +24,9 @@ pad_to_sequence_len: true
 lora_r: 8
 lora_alpha: 16
 lora_dropout: 0.05
+lora_target_modules:
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 relora_steps: 150
 relora_warmup_steps: 10
@@ -43,18 +45,28 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 10
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
   bos_token: "<s>"
   eos_token: "</s>"

examples/llama-3-vision/lora-11b.yaml

@@ -45,11 +45,14 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: true
 fp16:
 tf32: true
 
 gradient_checkpointing: true
+local_rank:
 logging_steps: 1
 flash_attention: true
 eager_attention:
@@ -57,4 +60,8 @@ eager_attention:
 warmup_ratio: 0.1
 evals_per_epoch: 1
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:

examples/llama-3/fft-8b-liger-fsdp.yaml

@@ -42,19 +42,27 @@ optimizer: adamw_torch_fused
 lr_scheduler: cosine
 learning_rate: 2e-5
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
 gradient_checkpointing_kwargs:
   use_reentrant: false
+early_stopping_patience:
 resume_from_checkpoint:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 100
 evals_per_epoch: 2
+eval_table_size:
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
 fsdp:
   - full_shard

examples/llama-3/fft-8b.yaml

@@ -1,6 +1,9 @@
 base_model: NousResearch/Meta-Llama-3.1-8B
 # Automatically upload checkpoint and final model to HF
 # hub_model_id: username/custom_model_name
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 datasets:
@@ -27,19 +30,29 @@ optimizer: paged_adamw_8bit
 lr_scheduler: cosine
 learning_rate: 2e-5
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
 gradient_checkpointing_kwargs:
   use_reentrant: false
+early_stopping_patience:
 resume_from_checkpoint:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 100
 evals_per_epoch: 2
+eval_table_size:
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
   pad_token: <|end_of_text|>

examples/llama-3/instruct-dpo-lora-8b.yml

@@ -42,6 +42,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -56,15 +57,31 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
+s2_attention:
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
+
+special_tokens:
+  pad_token: "<|end_of_text|>"

examples/llama-3/instruct-lora-8b.yml

@@ -37,6 +37,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -51,17 +52,30 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
+s2_attention:
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
    pad_token: <|end_of_text|>

examples/llama-3/lora-1b-deduplicate-dpo.yml

@@ -58,6 +58,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -72,15 +73,28 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
+s2_attention:
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:

examples/llama-3/lora-1b-deduplicate-sft.yml

@@ -31,6 +31,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 lora_modules_to_save:
   - embed_tokens
   - lm_head
@@ -48,17 +49,30 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
+s2_attention:
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
    pad_token: <|end_of_text|>

examples/llama-3/lora-1b-kernels.yml

@@ -1,6 +1,9 @@
 base_model: NousResearch/Llama-3.2-1B
 # Automatically upload checkpoint and final model to HF
 # hub_model_id: username/custom_model_name
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 datasets:
@@ -21,6 +24,7 @@ lora_r: 16
 lora_alpha: 32
 # Currently, we don't support dropout with our custom Triton kernels
 # lora_dropout: 0.05
+lora_fan_in_fan_out:
 lora_target_modules:
   - gate_proj
   - down_proj
@@ -49,12 +53,18 @@ optimizer: adamw_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 loss_watchdog_threshold: 5.0
@@ -63,6 +73,10 @@ loss_watchdog_patience: 3
 warmup_steps: 10
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
   pad_token: "<|end_of_text|>"

examples/llama-3/lora-1b-ray.yml

@@ -1,6 +1,9 @@
 base_model: NousResearch/Llama-3.2-1B
 # Automatically upload checkpoint and final model to HF
 # hub_model_id: username/custom_model_name
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 datasets:
@@ -21,6 +24,7 @@ pad_to_sequence_len: true
 lora_r: 16
 lora_alpha: 32
 lora_dropout: 0.05
+lora_fan_in_fan_out:
 lora_target_modules:
   - gate_proj
   - down_proj
@@ -43,12 +47,18 @@ optimizer: adamw_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 loss_watchdog_threshold: 5.0
@@ -57,9 +67,11 @@ loss_watchdog_patience: 3
 warmup_steps: 10
 evals_per_epoch: 4
 saves_per_epoch: 1
-
+debug:
 deepspeed: deepspeed_configs/zero3.json
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
   pad_token: "<|end_of_text|>"
 

examples/llama-3/lora-1b-sample-packing-sequentially.yml

@@ -33,6 +33,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 lora_modules_to_save:
   - embed_tokens
   - lm_head
@@ -50,17 +51,30 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
+s2_attention:
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
   pad_token: <|end_of_text|>

examples/llama-3/lora-1b.yml

@@ -1,6 +1,9 @@
 base_model: NousResearch/Llama-3.2-1B
 # Automatically upload checkpoint and final model to HF
 # hub_model_id: username/custom_model_name
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 datasets:
@@ -21,6 +24,7 @@ pad_to_sequence_len: true
 lora_r: 16
 lora_alpha: 32
 lora_dropout: 0.05
+lora_fan_in_fan_out:
 lora_target_modules:
   - gate_proj
   - down_proj
@@ -43,12 +47,18 @@ optimizer: adamw_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 loss_watchdog_threshold: 5.0
@@ -57,6 +67,10 @@ loss_watchdog_patience: 3
 warmup_steps: 10
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
   pad_token: "<|end_of_text|>"

examples/llama-3/lora-8b.yml

@@ -27,6 +27,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 lora_modules_to_save:
   - embed_tokens
   - lm_head
@@ -44,17 +45,30 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
+s2_attention:
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
    pad_token: <|end_of_text|>

examples/llama-3/qlora-1b-kto.yaml

@@ -32,6 +32,7 @@ lora_r: 32
 lora_alpha: 64
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -46,19 +47,31 @@ optimizer: adamw_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: true
 
 gradient_checkpointing: true
 gradient_checkpointing_kwargs:
   use_reentrant: false
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 20
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
   pad_token: "<|end_of_text|>"

examples/llama-3/qlora-1b.yml

@@ -24,6 +24,7 @@ pad_to_sequence_len: true
 lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
+lora_fan_in_fan_out:
 lora_target_modules:
   - gate_proj
   - down_proj
@@ -46,12 +47,18 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 loss_watchdog_threshold: 5.0
@@ -59,7 +66,13 @@ loss_watchdog_patience: 3
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
   pad_token: "<|end_of_text|>"

examples/llama-3/qlora-fsdp-405b.yaml

@@ -24,6 +24,7 @@ pad_to_sequence_len: true
 lora_r: 16
 lora_alpha: 16
 lora_dropout: 0.05
+lora_target_modules:
 lora_target_linear: true
 
 gradient_accumulation_steps: 4
@@ -33,6 +34,8 @@ optimizer: adamw_torch_fused
 lr_scheduler: cosine
 learning_rate: 0.00001
 
+train_on_inputs: false
+group_by_length: false
 bf16: true
 tf32: true
 

examples/llama-3/qlora-fsdp-70b.yaml

@@ -26,7 +26,9 @@ pad_to_sequence_len: true
 lora_r: 8
 lora_alpha: 16
 lora_dropout: 0.05
+lora_target_modules:
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -41,19 +43,28 @@ optimizer: adamw_torch_fused
 lr_scheduler: cosine
 learning_rate: 0.00001
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
 gradient_checkpointing_kwargs:
   use_reentrant: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
 fsdp:
   - full_shard

examples/llama-3/qlora.yml

@@ -26,7 +26,9 @@ pad_to_sequence_len: true
 lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
+lora_target_modules:
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -41,17 +43,28 @@ optimizer: paged_adamw_32bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
   pad_token: "<|end_of_text|>"

examples/llava/lora-7b.yaml

@@ -41,11 +41,14 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: true
 fp16:
 tf32: true
 
 gradient_checkpointing: true
+local_rank:
 logging_steps: 1
 flash_attention: true
 eager_attention:
@@ -53,4 +56,8 @@ eager_attention:
 warmup_ratio: 0.1
 evals_per_epoch: 1
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:

examples/mamba/config.yml

@@ -5,6 +5,9 @@ tokenizer_type: AutoTokenizer
 tokenizer_config: EleutherAI/gpt-neox-20b
 # Automatically upload checkpoint and final model to HF
 # hub_model_id: username/custom_model_name
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 datasets:
@@ -35,17 +38,27 @@ train_on_inputs: false
 group_by_length: true
 
 bf16: auto
+fp16:
 tf32: true
 
 gradient_checkpointing: false
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention:
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
 tokens:
 save_safetensors: False

examples/mistral/bigstral-ds-zero3.yaml

@@ -6,6 +6,9 @@ tokenizer_type: LlamaTokenizer
 # hub_model_id: username/custom_model_name
 
 trust_remote_code: true
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 unfrozen_parameters:
@@ -37,19 +40,27 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0001
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 save_total_limit: 1
 save_steps:
-
+debug:
 deepspeed: deepspeed_configs/zero3_bf16_cpuoffload_params.json
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
   eos_token: "<|im_end|>"
 tokens:

examples/mistral/config.yml

@@ -4,6 +4,9 @@ model_type: MistralForCausalLM
 tokenizer_type: LlamaTokenizer
 # Automatically upload checkpoint and final model to HF
 # hub_model_id: username/custom_model_name
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 datasets:
@@ -31,16 +34,28 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.000005
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:

examples/mistral/lora-mps.yml

@@ -4,6 +4,9 @@ model_type: MistralForCausalLM
 tokenizer_type: LlamaTokenizer
 # Automatically upload checkpoint and final model to HF
 # hub_model_id: username/custom_model_name
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 datasets:
@@ -25,6 +28,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 lora_target_modules:
   - gate_proj
   - down_proj
@@ -47,13 +51,18 @@ optimizer: adamw_torch_fused
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
 fp16: false
 tf32: true
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: false
 sdp_attention: true
 
@@ -62,6 +71,12 @@ loss_watchdog_patience: 3
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_table_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:

examples/mistral/lora.yml

@@ -27,6 +27,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 lora_target_modules:
   - gate_proj
   - down_proj
@@ -49,12 +50,18 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 loss_watchdog_threshold: 5.0
@@ -62,6 +69,12 @@ loss_watchdog_patience: 3
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:

examples/mistral/mistral-dpo-qlora.yml

@@ -40,6 +40,7 @@ lora_r: 8
 lora_alpha: 16
 lora_dropout: 0.2
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 lora_target_modules:
   - gate_proj
@@ -66,18 +67,31 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0001
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: false
+s2_attention:
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
   bos_token: "<|im_start|>"
   eos_token: "<|im_end|>"

examples/mistral/mistral-qlora-fsdp.yml

@@ -32,6 +32,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -46,12 +47,18 @@ optimizer: paged_adamw_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 loss_watchdog_threshold: 5.0
@@ -59,8 +66,10 @@ loss_watchdog_patience: 3
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
-
+debug:
 weight_decay: 0.0
 fsdp:
   - full_shard

examples/mistral/mistral-qlora-orpo.yml

@@ -32,6 +32,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 lora_target_modules:
   - gate_proj
   - down_proj
@@ -54,12 +55,18 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 loss_watchdog_threshold: 5.0
@@ -67,6 +74,12 @@ loss_watchdog_patience: 3
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:

examples/mistral/mistral-small-3.1-24B-lora.yml

@@ -43,11 +43,14 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: true
 fp16:
 tf32: true
 
 gradient_checkpointing: true
+local_rank:
 logging_steps: 1
 flash_attention: false # PixtralVisionModel does not support Flash Attention 2.0 yet.
 eager_attention:
@@ -55,5 +58,9 @@ eager_attention:
 warmup_ratio: 0.1
 evals_per_epoch: 1
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:

examples/mistral/mixtral-8x22b-qlora-fsdp.yml

@@ -30,6 +30,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -44,12 +45,18 @@ optimizer: adamw_torch_fused
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: true
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 loss_watchdog_threshold: 5.0
@@ -57,8 +64,10 @@ loss_watchdog_patience: 3
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
-
+debug:
 weight_decay: 0.0
 fsdp:
   - full_shard

examples/mistral/mixtral-qlora-fsdp.yml

@@ -32,6 +32,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -46,12 +47,18 @@ optimizer: adamw_torch_fused
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: true
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 loss_watchdog_threshold: 5.0
@@ -59,8 +66,10 @@ loss_watchdog_patience: 3
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
-
+debug:
 weight_decay: 0.0
 fsdp:
   - full_shard

examples/mistral/mixtral.yml

@@ -41,6 +41,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 #lora_target_modules:
 #  - gate
 #  - q_proj
@@ -64,12 +65,18 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 loss_watchdog_threshold: 5.0
@@ -77,8 +84,12 @@ loss_watchdog_patience: 3
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
-
+debug:
 deepspeed: deepspeed_configs/zero2.json
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:

examples/mistral/mixtral_22.yml

@@ -6,6 +6,9 @@ tokenizer_type: LlamaTokenizer
 # hub_model_id: username/custom_model_name
 
 trust_remote_code: true
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 unfrozen_parameters:
@@ -35,19 +38,27 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0001
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 save_total_limit: 1
 save_steps:
-
+debug:
 deepspeed: deepspeed_configs/zero3_bf16_cpuoffload_all.json
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
   eos_token: "<|im_end|>"
 tokens:

examples/mistral/qlora.yml

@@ -27,6 +27,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 lora_target_modules:
   - gate_proj
   - down_proj
@@ -49,12 +50,18 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 loss_watchdog_threshold: 5.0
@@ -62,6 +69,12 @@ loss_watchdog_patience: 3
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:

examples/mpt-7b/config.yml

@@ -35,17 +35,26 @@ optimizer: adamw_bnb_8bit
 torchdistx_path:
 lr_scheduler: cosine
 learning_rate: 0.0000002
+train_on_inputs: false
+group_by_length: false
 bf16: auto
 tf32: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 5
+xformers_attention:
 flash_attention:
 gptq_groupsize:
 gptq_model_v1:
 warmup_steps: 20
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0001
+fsdp:
+fsdp_config:
 tokens:
   pad_token: "<|padding|>"
   bos_token: "<|endoftext|>"

examples/openllama-3b/config.yml

@@ -4,6 +4,9 @@ model_type: LlamaForCausalLM
 tokenizer_type: LlamaTokenizer
 # Automatically upload checkpoint and final model to HF
 # hub_model_id: username/custom_model_name
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 push_dataset_to_hub:
 datasets:
@@ -20,6 +23,7 @@ lora_alpha:
 lora_dropout:
 lora_target_modules:
 lora_target_linear:
+lora_fan_in_fan_out:
 wandb_project:
 wandb_entity:
 wandb_watch:
@@ -33,20 +37,29 @@ optimizer: adamw_bnb_8bit
 torchdistx_path:
 lr_scheduler: cosine
 learning_rate: 0.000003
+train_on_inputs: false
+group_by_length: false
 float16: true
 bf16: false
 fp16: false
 tf32: false
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 gptq_groupsize:
 gptq_model_v1:
 warmup_steps: 20
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.1
+fsdp:
+fsdp_config:
 special_tokens:
   bos_token: "<s>"
   eos_token: "</s>"

examples/openllama-3b/lora.yml

@@ -29,6 +29,7 @@ lora_target_modules:
   - v_proj
   - k_proj
   - o_proj
+lora_fan_in_fan_out:
 wandb_project:
 wandb_entity:
 wandb_watch:
@@ -42,19 +43,29 @@ optimizer: adamw_bnb_8bit
 torchdistx_path:
 lr_scheduler: cosine
 learning_rate: 0.0002
+train_on_inputs: false
+group_by_length: false
 bf16: false
 fp16: true
 tf32: false
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 gptq_groupsize:
+s2_attention:
 gptq_model_v1:
 warmup_steps: 20
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.1
+fsdp:
+fsdp_config:
 special_tokens:
   bos_token: "<s>"
   eos_token: "</s>"

examples/openllama-3b/qlora.yml

@@ -21,7 +21,9 @@ sample_packing: true
 lora_r: 8
 lora_alpha: 32
 lora_dropout: 0.05
+lora_target_modules:
 lora_target_linear: true
+lora_fan_in_fan_out:
 wandb_project:
 wandb_entity:
 wandb_watch:
@@ -35,19 +37,28 @@ optimizer: paged_adamw_32bit
 torchdistx_path:
 lr_scheduler: cosine
 learning_rate: 0.0002
+train_on_inputs: false
+group_by_length: false
 bf16: false
 fp16: true
 tf32: false
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 gptq_groupsize:
 gptq_model_v1:
 warmup_steps: 20
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.1
+fsdp:
+fsdp_config:
 special_tokens:
   bos_token: "<s>"
   eos_token: "</s>"

examples/phi/lora-3.5.yaml

@@ -37,6 +37,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -51,16 +52,28 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bfloat16: true
 bf16: true
 fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
+s2_attention:
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 4
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:

examples/phi/phi-ft.yml

@@ -4,6 +4,9 @@ model_type: AutoModelForCausalLM
 tokenizer_type: AutoTokenizer
 # Automatically upload checkpoint and final model to HF
 # hub_model_id: username/custom_model_name
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 datasets:
@@ -24,6 +27,7 @@ lora_r:
 lora_alpha:
 lora_dropout:
 lora_target_linear:
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -41,20 +45,30 @@ max_grad_norm: 1.0
 lr_scheduler: cosine
 learning_rate: 0.000003
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: true
 
 gradient_checkpointing: true
 gradient_checkpointing_kwargs:
   use_reentrant: True
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 100
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.1
+fsdp:
+fsdp_config:
 resize_token_embeddings_to_32x: true
 special_tokens:
   pad_token: "<|endoftext|>"

examples/phi/phi-qlora.yml

@@ -27,6 +27,7 @@ lora_r: 64
 lora_alpha: 32
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -44,20 +45,30 @@ max_grad_norm: 1.0
 lr_scheduler: cosine
 learning_rate: 0.000003
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: true
 
 gradient_checkpointing: true
 gradient_checkpointing_kwargs:
   use_reentrant: True
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 100
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.1
+fsdp:
+fsdp_config:
 resize_token_embeddings_to_32x: true
 special_tokens:
   pad_token: "<|endoftext|>"

examples/phi/phi2-ft.yml

@@ -4,6 +4,9 @@ model_type: AutoModelForCausalLM
 tokenizer_type: AutoTokenizer
 # Automatically upload checkpoint and final model to HF
 # hub_model_id: username/custom_model_name
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 datasets:
@@ -24,6 +27,7 @@ lora_r:
 lora_alpha:
 lora_dropout:
 lora_target_linear:
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -41,20 +45,30 @@ max_grad_norm: 1.0
 lr_scheduler: cosine
 learning_rate: 0.000003
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: true
 
 gradient_checkpointing: true
 gradient_checkpointing_kwargs:
   use_reentrant: True
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 100
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.1
+fsdp:
+fsdp_config:
 resize_token_embeddings_to_32x: true
 special_tokens:
   pad_token: "<|endoftext|>"

examples/phi/phi3-ft-fsdp.yml

@@ -4,6 +4,9 @@ model_type: AutoModelForCausalLM
 tokenizer_type: AutoTokenizer
 # Automatically upload checkpoint and final model to HF
 # hub_model_id: username/custom_model_name
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 datasets:
@@ -25,6 +28,7 @@ lora_r:
 lora_alpha:
 lora_dropout:
 lora_target_linear:
+lora_fan_in_fan_out:
 
 wandb_project: phi3
 wandb_entity:
@@ -42,19 +46,27 @@ max_grad_norm: 1.0
 lr_scheduler: cosine
 learning_rate: 0.000003
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: true
 
 gradient_checkpointing: true
 gradient_checkpointing_kwargs:
   use_reentrant: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 100
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.1
 fsdp:
   - full_shard

examples/phi/phi3-ft.yml

@@ -7,6 +7,9 @@ tokenizer_type: AutoTokenizer
 # hub_model_id: username/custom_model_name
 
 chat_template: phi_3
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 datasets:
@@ -27,6 +30,7 @@ lora_r: 64
 lora_alpha: 32
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 gradient_accumulation_steps: 1
 micro_batch_size: 2
@@ -38,6 +42,8 @@ max_grad_norm: 1.0
 lr_scheduler: cosine
 learning_rate: 5.0e-6
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
 
 gradient_checkpointing: true
@@ -49,9 +55,9 @@ flash_attention: true
 
 eval_steps: 1000
 save_steps: 5000
+eval_table_size: 2
 eval_batch_size: 2
 eval_sample_packing: false
-eval_table_size: 2
 eval_max_new_tokens: 32
 eval_causal_lm_metrics: ["perplexity"]
 do_causal_lm_eval: true

examples/pixtral/lora-12b.yml

@@ -41,11 +41,14 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: true
 fp16:
 tf32: true
 
 gradient_checkpointing: true
+local_rank:
 logging_steps: 1
 flash_attention: false # PixtralVisionModel does not support Flash Attention 2.0 yet
 eager_attention:
@@ -53,6 +56,10 @@ eager_attention:
 warmup_ratio: 0.1
 evals_per_epoch: 1
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:
   pad_token: <pad>

examples/pythia-12b/config.yml

@@ -5,6 +5,9 @@ model_type: GPTNeoXForCausalLM
 tokenizer_type: AutoTokenizer
 # Automatically upload checkpoint and final model to HF
 # hub_model_id: username/custom_model_name
+
+load_in_8bit: false
+load_in_4bit: false
 gptq: false
 device_map: auto
 datasets:
@@ -19,6 +22,7 @@ max_packed_sequence_len: 2048
 lora_r: 64
 lora_alpha: 32
 lora_dropout: 0.0
+lora_target_modules:
 lora_target_linear: true
 lora_fan_in_fan_out: true  # pythia/GPTNeoX lora specific
 wandb_project:
@@ -33,10 +37,16 @@ num_epochs: 5
 learning_rate: 0.00003
 optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
+train_on_inputs: false
+group_by_length: false
 bf16: false
 fp16: false
 float16: true
 tf32: true
 flash_optimum: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 gradient_checkpointing: true
+fsdp:
+fsdp_config:

examples/pythia/lora.yml

@@ -28,9 +28,13 @@ gradient_accumulation_steps: 1
 micro_batch_size: 4
 num_epochs: 4
 learning_rate: 0.00001
+train_on_inputs: false
+group_by_length: false
 bf16: auto
 tf32: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 weight_decay: 0.1
 evals_per_epoch: 4
 logging_steps: 1

examples/qwen/lora.yml

@@ -28,6 +28,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -42,16 +43,28 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: false
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention:
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:

examples/qwen/qlora.yml

@@ -28,6 +28,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -42,16 +43,28 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: false
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention:
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:

examples/qwen/qwen2-moe-lora.yaml

@@ -3,6 +3,9 @@ base_model: Qwen/Qwen1.5-MoE-A2.7B
 # hub_model_id: username/custom_model_name
 
 trust_remote_code: true
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 datasets:
@@ -22,6 +25,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -36,18 +40,28 @@ optimizer: paged_adamw_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: true
 
 gradient_checkpointing: true
 gradient_checkpointing_kwargs:
   use_reentrant: false
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 10
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:

examples/qwen/qwen2-moe-qlora.yaml

@@ -25,6 +25,7 @@ lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -39,18 +40,28 @@ optimizer: paged_adamw_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: true
 
 gradient_checkpointing: true
 gradient_checkpointing_kwargs:
   use_reentrant: false
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 10
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:

examples/qwen2-vl/lora-7b.yaml

@@ -41,11 +41,14 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: true
 fp16:
 tf32: true
 
 gradient_checkpointing: true
+local_rank:
 logging_steps: 1
 flash_attention: true
 eager_attention:
@@ -53,4 +56,8 @@ eager_attention:
 warmup_ratio: 0.1
 evals_per_epoch: 1
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:

examples/qwen2/dpo.yaml

@@ -44,15 +44,27 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 10
 evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:

examples/qwen2/prm.yaml

@@ -5,6 +5,9 @@ num_labels: 2
 tokenizer_type: AutoTokenizer
 # Automatically upload checkpoint and final model to HF
 # hub_model_id: username/custom_model_name
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 process_reward_model: true
@@ -40,19 +43,30 @@ optimizer: adamw_torch
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: true
 fp16:
 tf32:
 gradient_checkpointing: true
 gradient_checkpointing_kwargs:
   use_reentrant: false
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_ratio: 0.1
 evals_per_epoch:
+eval_table_size:
+eval_max_new_tokens: 128
 eval_steps: 100
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:

examples/qwen2/qlora-fsdp.yaml

@@ -26,6 +26,7 @@ lora_r: 32
 lora_alpha: 64
 lora_dropout: 0.05
 lora_target_linear: true
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -40,19 +41,27 @@ optimizer: adamw_torch_fused
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: true
 
 gradient_checkpointing: true
 gradient_checkpointing_kwargs:
   use_reentrant: false
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_steps: 10
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
 fsdp:
   - full_shard

examples/qwen2/reward-model.yaml

@@ -5,6 +5,9 @@ num_labels: 1
 tokenizer_type: AutoTokenizer
 # Automatically upload checkpoint and final model to HF
 # hub_model_id: username/custom_model_name
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 reward_model: true
@@ -35,6 +38,8 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: true
 fp16:
 tf32: true
@@ -42,12 +47,21 @@ tf32: true
 gradient_checkpointing: true
 gradient_checkpointing_kwargs:
   use_reentrant: false
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 
 warmup_ratio: 0.1
 evals_per_epoch:
+eval_table_size:
+eval_max_new_tokens: 128
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0
+fsdp:
+fsdp_config:
 special_tokens:

examples/redpajama/config-3b.yml

@@ -36,17 +36,26 @@ optimizer: adamw_bnb_8bit
 torchdistx_path:
 lr_scheduler: cosine
 learning_rate: 0.0000002
+train_on_inputs: false
+group_by_length: false
 bf16: auto
 tf32: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 5
+xformers_attention:
 flash_attention:
 gptq_groupsize:
 gptq_model_v1:
 warmup_steps: 20
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0.0001
+fsdp:
+fsdp_config:
 tokens:
   pad_token: "<|padding|>"
   bos_token: "<|endoftext|>"

examples/replit-3b/config-lora.yml

@@ -20,6 +20,7 @@ lora_target_modules:
   - Wqkv
   - mlp_up
   - mlp_down
+lora_fan_in_fan_out:
 wandb_project: lora-replit
 wandb_entity:
 wandb_watch:
@@ -33,16 +34,25 @@ optimizer:
 torchdistx_path:
 lr_scheduler:
 learning_rate: 0.00001
+train_on_inputs: false
+group_by_length: false
 bf16: auto
 tf32: true
 gradient_checkpointing:
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention:
 gptq_groupsize:
 gptq_model_v1:
 warmup_steps: 20
 evals_per_epoch: 4
 saves_per_epoch: 1
+debug:
+deepspeed:
 weight_decay: 0
+fsdp:
+fsdp_config:
 #special_tokens:

examples/stablelm-2/1.6b/fft.yml

@@ -6,6 +6,9 @@ tokenizer_type: AutoTokenizer
 # hub_model_id: username/custom_model_name
 
 trust_remote_code: true
+
+load_in_8bit: false
+load_in_4bit: false
 strict: false
 
 datasets:
@@ -25,6 +28,7 @@ lora_r:
 lora_alpha:
 lora_dropout:
 lora_target_linear:
+lora_fan_in_fan_out:
 
 wandb_project:
 wandb_entity:
@@ -39,12 +43,18 @@ optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
+train_on_inputs: false
+group_by_length: false
 bf16: auto
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
 resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
 flash_attn_cross_entropy: false
 flash_attn_rms_norm: true
@@ -53,8 +63,11 @@ flash_attn_fuse_mlp: true
 
 warmup_steps: 100
 evals_per_epoch: 4
+eval_table_size:
 saves_per_epoch: 1
-
+debug:
 deepspeed: #deepspeed_configs/zero2.json # multi-gpu only
 weight_decay: 0.1
+fsdp:
+fsdp_config:
 special_tokens: