996fc124e5
* Add: SFTPlugin with llmcompressor * Update: review comments! * Add:llmcompressor instalable * pre commit hooks * Use: warning over warn * Revert: TODO's * Update llmcompressor version to latest * Apply suggestions from @markurtz Co-authored-by: Mark Kurtz <mark.j.kurtz@gmail.com> * Address review comments from @markurtz * Add: llcompressor installable * Rename: sft.yaml to sparse-finetuning.yaml * Use: absolute import * Update model config * Move: LLMCompressorPlugin into it's own submodule * Add: `llm_compressor` integration documentation * Rebase and updates! * Tests, Style, Updates * Add: .qmd file * Address Review Comments: * deleted redundant docs/llm_compressor.qmd * incorporated feedback in integration README.md * added llmcompressor integration to docs/custom_integrations.qmd Signed-off-by: Rahul Tuli <rtuli@redhat.com> * Add: line about further optimizations using llmcompressor Signed-off-by: Rahul Tuli <rtuli@redhat.com> * Apply patch from @winglian Signed-off-by: Rahul Tuli <rtuli@redhat.com> * Fix: Test Signed-off-by: Rahul Tuli <rtuli@redhat.com> * additional fixes for docker and saving compressed * split llmcompressor from vllm checks * Reset session between tests Signed-off-by: Rahul Tuli <rtuli@redhat.com> * move decorator to test method instead of class * make sure to reset the session after each test * move import of llmcompressor to reset session inside test --------- Signed-off-by: Rahul Tuli <rtuli@redhat.com> Co-authored-by: Mark Kurtz <mark.j.kurtz@gmail.com> Co-authored-by: Wing Lian <wing@axolotl.ai>
78 lines
1.5 KiB
YAML
78 lines
1.5 KiB
YAML
base_model: neuralmagic/Sparse-Llama-3.1-8B-2of4
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plugins:
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- axolotl.integrations.llm_compressor.LLMCompressorPlugin
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load_in_8bit: false
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load_in_4bit: false
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strict: false
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datasets:
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- path: tatsu-lab/alpaca
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type: alpaca
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.05
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output_dir: ./outputs/out
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sequence_len: 4096
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sample_packing: true
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pad_to_sequence_len: true
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eval_sample_packing: false
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wandb_project:
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wandb_entity:
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wandb_watch:
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wandb_name:
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wandb_log_model:
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gradient_accumulation_steps: 8
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micro_batch_size: 1
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num_epochs: 1
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optimizer: paged_adamw_8bit
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lr_scheduler: cosine
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learning_rate: 2e-5
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train_on_inputs: false
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group_by_length: false
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bf16: auto
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fp16:
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tf32: false
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gradient_checkpointing: true
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gradient_checkpointing_kwargs:
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use_reentrant: false
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early_stopping_patience:
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resume_from_checkpoint:
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logging_steps: 1
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xformers_attention:
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flash_attention: true
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warmup_steps: 100
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evals_per_epoch: 2
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eval_table_size:
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saves_per_epoch: 1
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debug:
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deepspeed:
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weight_decay: 0.0
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fsdp:
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fsdp_config:
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special_tokens:
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pad_token: <|end_of_text|>
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llmcompressor:
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recipe:
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finetuning_stage:
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finetuning_modifiers:
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ConstantPruningModifier:
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targets: [
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're:.*q_proj.weight',
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're:.*k_proj.weight',
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're:.*v_proj.weight',
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're:.*o_proj.weight',
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're:.*gate_proj.weight',
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're:.*up_proj.weight',
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're:.*down_proj.weight',
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]
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start: 0
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save_compressed: true
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