* add torch to requirements.txt at build time to force version to stick
* fix xformers check
* better handling of xformers based on installed torch version
* fix for ci w/o torch
* start at index 0
* add test to check for missing turns
* apply black
* Update test_prompt_tokenizers.py
* Update src/axolotl/monkeypatch/fastchat_conversation_turns.py
Co-authored-by: Motoki Wu <tokestermw@gmail.com>
* fix linting
* apply black
* add more tests for llama/sharegpt
* make logic clearer
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Co-authored-by: Motoki Wu <tokestermw@gmail.com>
* fix: switch to using the HuggingFace Transformers NEFT implementation
* linter
* add support for noisy_embedding_alpha with a warning about it being renamed
* restore pre/posttrain_hooks
* move validation of NEFT noise alpha into validate_config()
* linter
* add check for zero3
* freeze parameters
* fixes for deepspeed loading
* fix model parameter check
* unfrozen parameters in example mixtral and logging when unfreezing
* Respect sequence_len in config for `type: llama2_chat`
It was hardcoded to `4096` I am not sure why? This updates it to pull from the config.
cc: @winglian
* Update llama2_chat.py
* apply black formatting
* fix tokenizer
* update test data
* lint fixtures
* mixtral multipack
* use mixtral model
* sample yml
* calculate cu_seqlens properly
* use updated flash ettention setting
* attn var checks
* force use of flash attention 2 for packing
* lint
* disable future fix for now
* update support table
* support for mamba
* more mamba fixes
* use fork for mamba kwargs fix
* grad checkpointing doesn't work
* fix extras for mamaba
* mamba loss fix
* use fp32 and remove verbose logging
* mamba fixes
* fix collator for mamba
* set model_type on training_args
* don't save safetensors for mamba
* update mamba config to disable safetensor checkpooints, install for tests
* no evals for mamba tests
* handle save_pretrained
* handle unused safetensors arg
* feat: add check for quantized model
* chore: refactor and add another check
* Update src/axolotl/utils/models.py
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Co-authored-by: Wing Lian <wing.lian@gmail.com>
* Support device_map sequential (and others). Support max_memory in cfg.
* Update documentation in README accordingly.
* Update README.md
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Co-authored-by: Wing Lian <wing.lian@gmail.com>
* Feat: Update to handle wandb env better
* chore: rename wandb_run_id to wandb_name
* feat: add new recommendation and update config
* fix: indent and pop disabled env if project passed
* feat: test env set for wandb and recommendation
* feat: update to use wandb_name and allow id
* chore: add info to readme
* Determine FSDP/deepspeed settings on device select.
Without this, the OS env check for accelerate will fail.
* rename and move env setup call
* chore: lint
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Co-authored-by: Karl-Johan Alm <kalle@gmail.com>
Co-authored-by: Wing Lian <wing.lian@gmail.com>
* add phi modeling from hf
* update for packing and use new modeling class for phi
* update e2e tests for phi to use new model name
* update example phi to also use new phi model name
* use AutoModelForCausalLM for phi lora since sample packing isn't supported
* allow zero len dataset
* better handling and warning of small eval splits
* raise error if eval split is too small
* don't mess with calculating total num steps in distributed context
* fix eval_sample_packing training args logic
* isolate torch from the requirements.txt
* fix typo for removed line ending
* pin transformers and accelerate to latest releases
* try w auto-gptq==0.5.1
* update README to remove manual peft install
* pin xformers to 0.0.22
* bump flash-attn to 2.3.3
* pin flash attn to exact version
* allow overriding of model_config parameters from the YML
* remove old logging, update readme
* move the updating of model config to the load_model_config function
* add warning for deprecated rope_scaling in the root of the YML config
* use tensorboard to see if resume from checkpoint works
* make sure e2e test is either fp16 or bf16
* set max_steps and save limit so we have the checkpoint when testing resuming
* fix test parameters
