Feat: add kimi linear support (#3257)
* feat: add custom kimi linear patch [skip ci] * feat: add configuration file and fix import [skip ci] * fix: hijack tokenizer temporarily [skip ci] * chore: remove accidental commit * fix: attempt patch kimi remote * fix: kwargs passsed * fix: device for tensor * fix: aux loss calculation * feat: cleaned up patches order * fix: remove duplicate tokenizer patch * chore: add debug logs * chore: add debug logs * chore: debug * Revert "chore: add debug logs" This reverts commitda372a5f67. * Revert "chore: add debug logs" This reverts commit97d1de1d7c. * fix: KeyError: 'tokenization_kimi' * fix: support remote_model_id in cce patch * feat: add config preload patch * fix: use standard aux loss calc and updated modeling * fix: import * feat: add kimi-linear docs and example * chore: add note about moe kernels * feat: update cce to include kimi-linear * chore: lint * chore: update main readme * fix: patch mechanism to address comments * chore: lint * fix: tests * chore: cleanup comment
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examples/kimi-linear/kimi-48b-lora.yaml
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81
examples/kimi-linear/kimi-48b-lora.yaml
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base_model: moonshotai/Kimi-Linear-48B-A3B-Instruct
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# Automatically upload checkpoint and final model to HF
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# hub_model_id: username/custom_model_name
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trust_remote_code: true
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plugins:
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- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
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load_in_8bit: true
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load_in_4bit: false
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strict: false
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datasets:
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- path: fozziethebeat/alpaca_messages_2k_test
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type: chat_template
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split: train
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.2
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output_dir: ./outputs/lora-out
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adapter: lora
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lora_model_dir:
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sequence_len: 2048
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sample_packing: true
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pad_to_sequence_len: true
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lora_r: 16
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lora_alpha: 32
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lora_dropout: 0.05
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lora_fan_in_fan_out:
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lora_target_modules:
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- gate_proj
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- down_proj
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- up_proj
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- q_proj
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- v_proj
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- k_proj
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- o_proj
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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: 2
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micro_batch_size: 2
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num_epochs: 1
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optimizer: adamw_8bit
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lr_scheduler: cosine
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learning_rate: 0.0002
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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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early_stopping_patience:
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resume_from_checkpoint:
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local_rank:
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logging_steps: 1
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flash_attention: true
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loss_watchdog_threshold: 5.0
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loss_watchdog_patience: 3
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warmup_ratio: 0.1
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evals_per_epoch: 2
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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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