Fix(doc): Minor doc changes for peft and modal (#2462) [skip ci]
* fix(doc): document peft configs * fix(doc): explain modal env vs secrets difference * fix(doc): clarify evaluate vs lm-eval * fix: clarify what is performance
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@@ -354,7 +354,27 @@ lora_target_modules:
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# - down_proj
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# - up_proj
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lora_target_linear: # If true, will target all linear modules
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peft_layers_to_transform: # The layer indices to transform, otherwise, apply to all layers
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# List[int] | int. # The layer indices to transform, otherwise, apply to all layers
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# https://huggingface.co/docs/peft/v0.15.0/en/package_reference/lora#peft.LoraConfig.layers_to_transform
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peft_layers_to_transform:
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# Optional[bool]. Whether to use DoRA.
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# https://huggingface.co/docs/peft/v0.15.0/en/developer_guides/lora#weight-decomposed-low-rank-adaptation-dora
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peft_use_dora:
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# Optional[bool]. Whether to use RSLoRA.
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# https://huggingface.co/docs/peft/v0.15.0/en/developer_guides/lora#rank-stabilized-lora
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peft_use_rslora:
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# Optional[list[tuple[int, int]]]. List of layer indices to replicate.
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# https://huggingface.co/docs/peft/v0.15.0/en/developer_guides/lora#memory-efficient-layer-replication-with-lora
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peft_layer_replication:
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# bool | Literal["gaussian", "eva", "olora", "pissa", "pissa_niter_[number of iters]", "corda", "loftq"]
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# How to initialize LoRA weights. Default to True which is MS original implementation.
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# https://huggingface.co/docs/peft/v0.15.0/en/developer_guides/lora#initialization
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peft_init_lora_weights:
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# If you added new tokens to the tokenizer, you may need to save some LoRA modules because they need to know the new tokens.
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# For LLaMA and Mistral, you need to save `embed_tokens` and `lm_head`. It may vary for other models.
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