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lora modules: all by default

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hiyouga 2024-06-06 03:53:28 +08:00
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56
README.md
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@ -149,34 +149,34 @@ Compared to ChatGLM's [P-Tuning](https://github.com/THUDM/ChatGLM2-6B/tree/main/
## Supported Models
| Model | Model size | Default module | Template |
| -------------------------------------------------------- | -------------------------------- | ----------------- | --------- |
| [Baichuan2](https://huggingface.co/baichuan-inc) | 7B/13B | W_pack | baichuan2 |
| [BLOOM](https://huggingface.co/bigscience) | 560M/1.1B/1.7B/3B/7.1B/176B | query_key_value | - |
| [BLOOMZ](https://huggingface.co/bigscience) | 560M/1.1B/1.7B/3B/7.1B/176B | query_key_value | - |
| [ChatGLM3](https://huggingface.co/THUDM) | 6B | query_key_value | chatglm3 |
| [Command-R](https://huggingface.co/CohereForAI) | 35B/104B | q_proj,v_proj | cohere |
| [DeepSeek (MoE)](https://huggingface.co/deepseek-ai) | 7B/16B/67B/236B | q_proj,v_proj | deepseek |
| [Falcon](https://huggingface.co/tiiuae) | 7B/11B/40B/180B | query_key_value | falcon |
| [Gemma/CodeGemma](https://huggingface.co/google) | 2B/7B | q_proj,v_proj | gemma |
| [GLM4](https://huggingface.co/THUDM) | 9B | query_key_value | glm4 |
| [InternLM2](https://huggingface.co/internlm) | 7B/20B | wqkv | intern2 |
| [LLaMA](https://github.com/facebookresearch/llama) | 7B/13B/33B/65B | q_proj,v_proj | - |
| [LLaMA-2](https://huggingface.co/meta-llama) | 7B/13B/70B | q_proj,v_proj | llama2 |
| [LLaMA-3](https://huggingface.co/meta-llama) | 8B/70B | q_proj,v_proj | llama3 |
| [LLaVA-1.5](https://huggingface.co/llava-hf) | 7B/13B | q_proj,v_proj | vicuna |
| [Mistral/Mixtral](https://huggingface.co/mistralai) | 7B/8x7B/8x22B | q_proj,v_proj | mistral |
| [OLMo](https://huggingface.co/allenai) | 1B/7B | q_proj,v_proj | - |
| [PaliGemma](https://huggingface.co/google) | 3B | q_proj,v_proj | gemma |
| [Phi-1.5/2](https://huggingface.co/microsoft) | 1.3B/2.7B | q_proj,v_proj | - |
| [Phi-3](https://huggingface.co/microsoft) | 4B/7B/14B | qkv_proj | phi |
| [Qwen](https://huggingface.co/Qwen) | 1.8B/7B/14B/72B | c_attn | qwen |
| [Qwen1.5 (Code/MoE)](https://huggingface.co/Qwen) | 0.5B/1.8B/4B/7B/14B/32B/72B/110B | q_proj,v_proj | qwen |
| [StarCoder2](https://huggingface.co/bigcode) | 3B/7B/15B | q_proj,v_proj | - |
| [XVERSE](https://huggingface.co/xverse) | 7B/13B/65B | q_proj,v_proj | xverse |
| [Yi (1/1.5)](https://huggingface.co/01-ai) | 6B/9B/34B | q_proj,v_proj | yi |
| [Yi-VL](https://huggingface.co/01-ai) | 6B/34B | q_proj,v_proj | yi_vl |
| [Yuan](https://huggingface.co/IEITYuan) | 2B/51B/102B | q_proj,v_proj | yuan |
| Model | Model size | Template |
| -------------------------------------------------------- | -------------------------------- | --------- |
| [Baichuan2](https://huggingface.co/baichuan-inc) | 7B/13B | baichuan2 |
| [BLOOM](https://huggingface.co/bigscience) | 560M/1.1B/1.7B/3B/7.1B/176B | - |
| [BLOOMZ](https://huggingface.co/bigscience) | 560M/1.1B/1.7B/3B/7.1B/176B | - |
| [ChatGLM3](https://huggingface.co/THUDM) | 6B | chatglm3 |
| [Command-R](https://huggingface.co/CohereForAI) | 35B/104B | cohere |
| [DeepSeek (MoE)](https://huggingface.co/deepseek-ai) | 7B/16B/67B/236B | deepseek |
| [Falcon](https://huggingface.co/tiiuae) | 7B/11B/40B/180B | falcon |
| [Gemma/CodeGemma](https://huggingface.co/google) | 2B/7B | gemma |
| [GLM4](https://huggingface.co/THUDM) | 9B | glm4 |
| [InternLM2](https://huggingface.co/internlm) | 7B/20B | intern2 |
| [LLaMA](https://github.com/facebookresearch/llama) | 7B/13B/33B/65B | - |
| [LLaMA-2](https://huggingface.co/meta-llama) | 7B/13B/70B | llama2 |
| [LLaMA-3](https://huggingface.co/meta-llama) | 8B/70B | llama3 |
| [LLaVA-1.5](https://huggingface.co/llava-hf) | 7B/13B | vicuna |
| [Mistral/Mixtral](https://huggingface.co/mistralai) | 7B/8x7B/8x22B | mistral |
| [OLMo](https://huggingface.co/allenai) | 1B/7B | - |
| [PaliGemma](https://huggingface.co/google) | 3B | gemma |
| [Phi-1.5/2](https://huggingface.co/microsoft) | 1.3B/2.7B | - |
| [Phi-3](https://huggingface.co/microsoft) | 4B/7B/14B | phi |
| [Qwen](https://huggingface.co/Qwen) | 1.8B/7B/14B/72B | qwen |
| [Qwen1.5 (Code/MoE)](https://huggingface.co/Qwen) | 0.5B/1.8B/4B/7B/14B/32B/72B/110B | qwen |
| [StarCoder2](https://huggingface.co/bigcode) | 3B/7B/15B | - |
| [XVERSE](https://huggingface.co/xverse) | 7B/13B/65B | xverse |
| [Yi (1/1.5)](https://huggingface.co/01-ai) | 6B/9B/34B | yi |
| [Yi-VL](https://huggingface.co/01-ai) | 6B/34B | yi_vl |
| [Yuan](https://huggingface.co/IEITYuan) | 2B/51B/102B | yuan |
> [!NOTE]
> **Default module** is used for the `lora_target` argument, you can use `lora_target: all` to specify all the available modules for better convergence.

60
README_zh.md
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@ -149,41 +149,39 @@ https://github.com/hiyouga/LLaMA-Factory/assets/16256802/ec36a9dd-37f4-4f72-81bd
## 模型
| 模型名 | 模型大小 | 默认模块 | Template |
| -------------------------------------------------------- | -------------------------------- | ----------------- | --------- |
| [Baichuan2](https://huggingface.co/baichuan-inc) | 7B/13B | W_pack | baichuan2 |
| [BLOOM](https://huggingface.co/bigscience) | 560M/1.1B/1.7B/3B/7.1B/176B | query_key_value | - |
| [BLOOMZ](https://huggingface.co/bigscience) | 560M/1.1B/1.7B/3B/7.1B/176B | query_key_value | - |
| [ChatGLM3](https://huggingface.co/THUDM) | 6B | query_key_value | chatglm3 |
| [Command-R](https://huggingface.co/CohereForAI) | 35B/104B | q_proj,v_proj | cohere |
| [DeepSeek (MoE)](https://huggingface.co/deepseek-ai) | 7B/16B/67B/236B | q_proj,v_proj | deepseek |
| [Falcon](https://huggingface.co/tiiuae) | 7B/11B/40B/180B | query_key_value | falcon |
| [Gemma/CodeGemma](https://huggingface.co/google) | 2B/7B | q_proj,v_proj | gemma |
| [GLM4](https://huggingface.co/THUDM) | 9B | query_key_value | glm4 |
| [InternLM2](https://huggingface.co/internlm) | 7B/20B | wqkv | intern2 |
| [LLaMA](https://github.com/facebookresearch/llama) | 7B/13B/33B/65B | q_proj,v_proj | - |
| [LLaMA-2](https://huggingface.co/meta-llama) | 7B/13B/70B | q_proj,v_proj | llama2 |
| [LLaMA-3](https://huggingface.co/meta-llama) | 8B/70B | q_proj,v_proj | llama3 |
| [LLaVA-1.5](https://huggingface.co/llava-hf) | 7B/13B | q_proj,v_proj | vicuna |
| [Mistral/Mixtral](https://huggingface.co/mistralai) | 7B/8x7B/8x22B | q_proj,v_proj | mistral |
| [OLMo](https://huggingface.co/allenai) | 1B/7B | q_proj,v_proj | - |
| [PaliGemma](https://huggingface.co/google) | 3B | q_proj,v_proj | gemma |
| [Phi-1.5/2](https://huggingface.co/microsoft) | 1.3B/2.7B | q_proj,v_proj | - |
| [Phi-3](https://huggingface.co/microsoft) | 4B/7B/14B | qkv_proj | phi |
| [Qwen](https://huggingface.co/Qwen) | 1.8B/7B/14B/72B | c_attn | qwen |
| [Qwen1.5 (Code/MoE)](https://huggingface.co/Qwen) | 0.5B/1.8B/4B/7B/14B/32B/72B/110B | q_proj,v_proj | qwen |
| [StarCoder2](https://huggingface.co/bigcode) | 3B/7B/15B | q_proj,v_proj | - |
| [XVERSE](https://huggingface.co/xverse) | 7B/13B/65B | q_proj,v_proj | xverse |
| [Yi (1/1.5)](https://huggingface.co/01-ai) | 6B/9B/34B | q_proj,v_proj | yi |
| [Yi-VL](https://huggingface.co/01-ai) | 6B/34B | q_proj,v_proj | yi_vl |
| [Yuan](https://huggingface.co/IEITYuan) | 2B/51B/102B | q_proj,v_proj | yuan |
| 模型名 | 模型大小 | Template |
| -------------------------------------------------------- | -------------------------------- | --------- |
| [Baichuan2](https://huggingface.co/baichuan-inc) | 7B/13B | baichuan2 |
| [BLOOM](https://huggingface.co/bigscience) | 560M/1.1B/1.7B/3B/7.1B/176B | - |
| [BLOOMZ](https://huggingface.co/bigscience) | 560M/1.1B/1.7B/3B/7.1B/176B | - |
| [ChatGLM3](https://huggingface.co/THUDM) | 6B | chatglm3 |
| [Command-R](https://huggingface.co/CohereForAI) | 35B/104B | cohere |
| [DeepSeek (MoE)](https://huggingface.co/deepseek-ai) | 7B/16B/67B/236B | deepseek |
| [Falcon](https://huggingface.co/tiiuae) | 7B/11B/40B/180B | falcon |
| [Gemma/CodeGemma](https://huggingface.co/google) | 2B/7B | gemma |
| [GLM4](https://huggingface.co/THUDM) | 9B | glm4 |
| [InternLM2](https://huggingface.co/internlm) | 7B/20B | intern2 |
| [LLaMA](https://github.com/facebookresearch/llama) | 7B/13B/33B/65B | - |
| [LLaMA-2](https://huggingface.co/meta-llama) | 7B/13B/70B | llama2 |
| [LLaMA-3](https://huggingface.co/meta-llama) | 8B/70B | llama3 |
| [LLaVA-1.5](https://huggingface.co/llava-hf) | 7B/13B | vicuna |
| [Mistral/Mixtral](https://huggingface.co/mistralai) | 7B/8x7B/8x22B | mistral |
| [OLMo](https://huggingface.co/allenai) | 1B/7B | - |
| [PaliGemma](https://huggingface.co/google) | 3B | gemma |
| [Phi-1.5/2](https://huggingface.co/microsoft) | 1.3B/2.7B | - |
| [Phi-3](https://huggingface.co/microsoft) | 4B/7B/14B | phi |
| [Qwen](https://huggingface.co/Qwen) | 1.8B/7B/14B/72B | qwen |
| [Qwen1.5 (Code/MoE)](https://huggingface.co/Qwen) | 0.5B/1.8B/4B/7B/14B/32B/72B/110B | qwen |
| [StarCoder2](https://huggingface.co/bigcode) | 3B/7B/15B | - |
| [XVERSE](https://huggingface.co/xverse) | 7B/13B/65B | xverse |
| [Yi (1/1.5)](https://huggingface.co/01-ai) | 6B/9B/34B | yi |
| [Yi-VL](https://huggingface.co/01-ai) | 6B/34B | yi_vl |
| [Yuan](https://huggingface.co/IEITYuan) | 2B/51B/102B | yuan |
> [!NOTE]
> **默认模块**应作为 `lora_target` 参数的默认值，可使用 `lora_target: all` 参数指定全部模块以取得更好的效果。
>
> 对于所有“基座”（Base）模型，`template` 参数可以是 `default`, `alpaca`, `vicuna` 等任意值。但“对话”（Instruct/Chat）模型请务必使用**对应的模板**。
>
> 请务必在训练和推理时使用**完全一致**的模板。
> 请务必在训练和推理时采用**完全一致**的模板。
项目所支持模型的完整列表请参阅 [constants.py](src/llamafactory/extras/constants.py)。

2
examples/extras/fsdp_qlora/llama3_lora_sft.yaml
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@ -6,7 +6,7 @@ quantization_bit: 4
stage: sft
do_train: true
finetuning_type: lora
lora_target: q_proj,v_proj
lora_target: all
### ddp
ddp_timeout: 180000000

2
examples/extras/loraplus/llama3_lora_sft.yaml
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@ -5,7 +5,7 @@ model_name_or_path: meta-llama/Meta-Llama-3-8B-Instruct
stage: sft
do_train: true
finetuning_type: lora
lora_target: q_proj,v_proj
lora_target: all
loraplus_lr_ratio: 16.0
### dataset

2
examples/lora_multi_gpu/llama3_lora_sft.yaml
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@ -5,7 +5,7 @@ model_name_or_path: meta-llama/Meta-Llama-3-8B-Instruct
stage: sft
do_train: true
finetuning_type: lora
lora_target: q_proj,v_proj
lora_target: all
### ddp
ddp_timeout: 180000000

2
examples/lora_multi_gpu/llama3_lora_sft_ds.yaml
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@ -5,7 +5,7 @@ model_name_or_path: meta-llama/Meta-Llama-3-8B-Instruct
stage: sft
do_train: true
finetuning_type: lora
lora_target: q_proj,v_proj
lora_target: all
### ddp
ddp_timeout: 180000000

2
examples/lora_multi_npu/llama3_lora_sft_ds.yaml
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@ -5,7 +5,7 @@ model_name_or_path: meta-llama/Meta-Llama-3-8B-Instruct
stage: sft
do_train: true
finetuning_type: lora
lora_target: q_proj,v_proj
lora_target: all
### ddp
ddp_timeout: 180000000

2
examples/lora_single_gpu/llama3_lora_dpo.yaml
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@ -5,7 +5,7 @@ model_name_or_path: meta-llama/Meta-Llama-3-8B-Instruct
stage: dpo
do_train: true
finetuning_type: lora
lora_target: q_proj,v_proj
lora_target: all
pref_beta: 0.1
pref_loss: sigmoid # [sigmoid (dpo), orpo, simpo]

2
examples/lora_single_gpu/llama3_lora_kto.yaml
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@ -5,7 +5,7 @@ model_name_or_path: meta-llama/Meta-Llama-3-8B-Instruct
stage: kto
do_train: true
finetuning_type: lora
lora_target: q_proj,v_proj
lora_target: all
### dataset
dataset: kto_en_demo

2
examples/lora_single_gpu/llama3_lora_ppo.yaml
View File

@ -6,7 +6,7 @@ reward_model: saves/llama3-8b/lora/reward
stage: ppo
do_train: true
finetuning_type: lora
lora_target: q_proj,v_proj
lora_target: all
### dataset
dataset: identity,alpaca_en_demo

2
examples/lora_single_gpu/llama3_lora_pretrain.yaml
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@ -5,7 +5,7 @@ model_name_or_path: meta-llama/Meta-Llama-3-8B-Instruct
stage: pt
do_train: true
finetuning_type: lora
lora_target: q_proj,v_proj
lora_target: all
### dataset
dataset: c4_demo

2
examples/lora_single_gpu/llama3_lora_reward.yaml
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@ -5,7 +5,7 @@ model_name_or_path: meta-llama/Meta-Llama-3-8B-Instruct
stage: rm
do_train: true
finetuning_type: lora
lora_target: q_proj,v_proj
lora_target: all
### dataset
dataset: dpo_en_demo

2
examples/lora_single_gpu/llama3_lora_sft.yaml
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@ -5,7 +5,7 @@ model_name_or_path: meta-llama/Meta-Llama-3-8B-Instruct
stage: sft
do_train: true
finetuning_type: lora
lora_target: q_proj,v_proj
lora_target: all
### dataset
dataset: identity,alpaca_en_demo

2
examples/lora_single_gpu/llama3_preprocess.yaml
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@ -5,7 +5,7 @@ model_name_or_path: meta-llama/Meta-Llama-3-8B-Instruct
stage: sft
do_train: true
finetuning_type: lora
lora_target: q_proj,v_proj
lora_target: all
### dataset
dataset: identity,alpaca_en_demo

2
examples/lora_single_gpu/llava1_5_lora_sft.yaml
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@ -6,7 +6,7 @@ visual_inputs: true
stage: sft
do_train: true
finetuning_type: lora
lora_target: q_proj,v_proj
lora_target: all
### dataset
dataset: mllm_demo

2
examples/qlora_single_gpu/llama3_lora_sft_aqlm.yaml
View File

@ -5,7 +5,7 @@ model_name_or_path: ISTA-DASLab/Meta-Llama-3-8B-Instruct-AQLM-2Bit-1x16
stage: sft
do_train: true
finetuning_type: lora
lora_target: q_proj,v_proj
lora_target: all
### dataset
dataset: identity,alpaca_en_demo

2
examples/qlora_single_gpu/llama3_lora_sft_awq.yaml
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@ -5,7 +5,7 @@ model_name_or_path: TechxGenus/Meta-Llama-3-8B-Instruct-AWQ
stage: sft
do_train: true
finetuning_type: lora
lora_target: q_proj,v_proj
lora_target: all
### dataset
dataset: identity,alpaca_en_demo

2
examples/qlora_single_gpu/llama3_lora_sft_bitsandbytes.yaml
View File

@ -6,7 +6,7 @@ quantization_bit: 4
stage: sft
do_train: true
finetuning_type: lora
lora_target: q_proj,v_proj
lora_target: all
### dataset
dataset: identity,alpaca_en_demo

2
examples/qlora_single_gpu/llama3_lora_sft_gptq.yaml
View File

@ -5,7 +5,7 @@ model_name_or_path: TechxGenus/Meta-Llama-3-8B-Instruct-GPTQ
stage: sft
do_train: true
finetuning_type: lora
lora_target: q_proj,v_proj
lora_target: all
### dataset
dataset: identity,alpaca_en_demo

19
src/llamafactory/extras/constants.py
View File

@ -20,8 +20,6 @@ CHOICES = ["A", "B", "C", "D"]
DATA_CONFIG = "dataset_info.json"
DEFAULT_MODULE = defaultdict(str)
DEFAULT_TEMPLATE = defaultdict(str)
FILEEXT2TYPE = {
@ -80,7 +78,6 @@ class DownloadSource(str, Enum):
def register_model_group(
models: Dict[str, Dict[DownloadSource, str]],
module: Optional[str] = None,
template: Optional[str] = None,
vision: bool = False,
) -> None:
@ -91,8 +88,6 @@ def register_model_group(
else:
assert prefix == name.split("-")[0], "prefix should be identical."
SUPPORTED_MODELS[name] = path
if module is not None:
DEFAULT_MODULE[prefix] = module
if template is not None:
DEFAULT_TEMPLATE[prefix] = template
if vision:
@ -127,7 +122,6 @@ register_model_group(
DownloadSource.MODELSCOPE: "baichuan-inc/Baichuan-13B-Chat",
},
},
module="W_pack",
template="baichuan",
)
@ -151,7 +145,6 @@ register_model_group(
DownloadSource.MODELSCOPE: "baichuan-inc/Baichuan2-13B-Chat",
},
},
module="W_pack",
template="baichuan2",
)
@ -171,7 +164,6 @@ register_model_group(
DownloadSource.MODELSCOPE: "AI-ModelScope/bloom-7b1",
},
},
module="query_key_value",
)
@ -190,7 +182,6 @@ register_model_group(
DownloadSource.MODELSCOPE: "AI-ModelScope/bloomz-7b1-mt",
},
},
module="query_key_value",
)
@ -229,7 +220,6 @@ register_model_group(
DownloadSource.MODELSCOPE: "ZhipuAI/chatglm2-6b",
}
},
module="query_key_value",
template="chatglm2",
)
@ -245,7 +235,6 @@ register_model_group(
DownloadSource.MODELSCOPE: "ZhipuAI/chatglm3-6b",
},
},
module="query_key_value",
template="chatglm3",
)
@ -344,7 +333,6 @@ register_model_group(
DownloadSource.MODELSCOPE: "AI-ModelScope/dbrx-instruct",
},
},
module="Wqkv",
template="dbrx",
)
@ -463,7 +451,6 @@ register_model_group(
DownloadSource.MODELSCOPE: "modelscope/falcon-180B-chat",
},
},
module="query_key_value",
template="falcon",
)
@ -512,7 +499,6 @@ register_model_group(
DownloadSource.MODELSCOPE: "ZhipuAI/glm-4-9b-chat-1m",
},
},
module="query_key_value",
template="glm4",
)
@ -559,7 +545,6 @@ register_model_group(
DownloadSource.MODELSCOPE: "Shanghai_AI_Laboratory/internlm2-chat-20b",
},
},
module="wqkv",
template="intern2",
)
@ -581,7 +566,6 @@ register_model_group(
DownloadSource.MODELSCOPE: "DeepLang/LingoWhale-8B",
}
},
module="qkv_proj",
)
@ -868,7 +852,6 @@ register_model_group(
DownloadSource.MODELSCOPE: "LLM-Research/Phi-3-medium-128k-instruct",
},
},
module="qkv_proj",
template="phi",
)
@ -940,7 +923,6 @@ register_model_group(
DownloadSource.MODELSCOPE: "qwen/Qwen-72B-Chat-Int4",
},
},
module="c_attn",
template="qwen",
)
@ -1153,7 +1135,6 @@ register_model_group(
DownloadSource.MODELSCOPE: "TeleAI/TeleChat-12B-v2",
},
},
module="query,key_value",
template="telechat",
)

15
src/llamafactory/hparams/finetuning_args.py
View File

@ -24,12 +24,7 @@ class FreezeArguments:
"help": (
"Name(s) of trainable modules for freeze (partial-parameter) fine-tuning. "
"Use commas to separate multiple modules. "
"Use `all` to specify all the available modules. "
"LLaMA choices: [`mlp`, `self_attn`], "
"BLOOM & Falcon & ChatGLM choices: [`mlp`, `self_attention`], "
"Qwen choices: [`mlp`, `attn`], "
"InternLM2 choices: [`feed_forward`, `attention`], "
"Others choices: the same as LLaMA."
"Use `all` to specify all the available modules."
)
},
)
@ -79,13 +74,7 @@ class LoraArguments:
"help": (
"Name(s) of target modules to apply LoRA. "
"Use commas to separate multiple modules. "
"Use `all` to specify all the linear modules. "
"LLaMA choices: [`q_proj`, `k_proj`, `v_proj`, `o_proj`, `gate_proj`, `up_proj`, `down_proj`], "
"BLOOM & Falcon & ChatGLM choices: [`query_key_value`, `dense`, `dense_h_to_4h`, `dense_4h_to_h`], "
"Baichuan choices: [`W_pack`, `o_proj`, `gate_proj`, `up_proj`, `down_proj`], "
"Qwen choices: [`c_attn`, `attn.c_proj`, `w1`, `w2`, `mlp.c_proj`], "
"InternLM2 choices: [`wqkv`, `wo`, `w1`, `w2`, `w3`], "
"Others choices: the same as LLaMA."
"Use `all` to specify all the linear modules."
)
},
)

8
src/llamafactory/webui/common.py
View File

@ -8,7 +8,6 @@ from yaml import safe_dump, safe_load
from ..extras.constants import (
CHECKPOINT_NAMES,
DATA_CONFIG,
DEFAULT_MODULE,
DEFAULT_TEMPLATE,
PEFT_METHODS,
STAGES_USE_PAIR_DATA,
@ -118,13 +117,6 @@ def get_model_info(model_name: str) -> Tuple[str, str, bool]:
return get_model_path(model_name), get_template(model_name), get_visual(model_name)
def get_module(model_name: str) -> str:
r"""
Gets the LoRA modules of this model.
"""
return DEFAULT_MODULE.get(get_prefix(model_name), "all")
def get_template(model_name: str) -> str:
r"""
Gets the template name if the model is a chat model.

4
src/llamafactory/webui/runner.py
View File

@ -8,7 +8,7 @@ from transformers.trainer import TRAINING_ARGS_NAME
from ..extras.constants import PEFT_METHODS, TRAINING_STAGES
from ..extras.misc import is_gpu_or_npu_available, torch_gc
from ..extras.packages import is_gradio_available
from .common import DEFAULT_CACHE_DIR, get_module, get_save_dir, load_config
from .common import DEFAULT_CACHE_DIR, get_save_dir, load_config
from .locales import ALERTS
from .utils import abort_leaf_process, gen_cmd, get_eval_results, get_trainer_info, load_args, save_args, save_cmd
@ -159,7 +159,7 @@ class Runner:
args["create_new_adapter"] = get("train.create_new_adapter")
args["use_rslora"] = get("train.use_rslora")
args["use_dora"] = get("train.use_dora")
args["lora_target"] = get("train.lora_target") or get_module(model_name)
args["lora_target"] = get("train.lora_target") or "all"
args["additional_target"] = get("train.additional_target") or None
if args["use_llama_pro"]: