update template
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@ -58,7 +58,7 @@
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| [Baichuan](https://github.com/baichuan-inc/baichuan-13B) | 7B/13B | W_pack | baichuan |
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| [InternLM](https://github.com/InternLM/InternLM) | 7B | q_proj,v_proj | intern |
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| [Qwen](https://github.com/QwenLM/Qwen-7B) | 7B | c_attn | chatml |
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| [XVERSE](https://github.com/xverse-ai/XVERSE-13B) | 13B | q_proj,v_proj | - |
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| [XVERSE](https://github.com/xverse-ai/XVERSE-13B) | 13B | q_proj,v_proj | xverse |
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| [ChatGLM2](https://github.com/THUDM/ChatGLM2-6B) | 6B | query_key_value | chatglm2 |
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- **Default module** is used for the `--lora_target` argument. Please use `python src/train_bash.py -h` to see all available options.
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@ -58,7 +58,7 @@
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| [Baichuan](https://github.com/baichuan-inc/baichuan-13B) | 7B/13B | W_pack | baichuan |
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| [InternLM](https://github.com/InternLM/InternLM) | 7B | q_proj,v_proj | intern |
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| [Qwen](https://github.com/QwenLM/Qwen-7B) | 7B | c_attn | chatml |
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| [XVERSE](https://github.com/xverse-ai/XVERSE-13B) | 13B | q_proj,v_proj | - |
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| [XVERSE](https://github.com/xverse-ai/XVERSE-13B) | 13B | q_proj,v_proj | xverse |
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| [ChatGLM2](https://github.com/THUDM/ChatGLM2-6B) | 6B | query_key_value | chatglm2 |
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- **默认模块**是 `--lora_target` 参数的部分可选项。请使用 `python src/train_bash.py -h` 查看全部可选项。
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@ -17,14 +17,15 @@ If you are using a custom dataset, please provide your dataset definition in the
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where the `prompt` and `response` columns should contain non-empty values. The `query` column will be concatenated with the `prompt` column and used as input for the model. The `history` column should contain a list where each element is a string tuple representing a query-response pair.
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For Reward-Modeling(rm) dataset, the first n examples represent chosen examples and the last n examples represent rejected examples.
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For datasets used in reward modeling or DPO training, the `response` column should be a string list, with the preferred answers appearing first, for example:
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```json
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{
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"instruction": "Question?",
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"input": "",
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"output": [
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"chosen answer",
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"rejected answer"
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]
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"instruction": "Question",
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"input": "",
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"output": [
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"Chosen answer",
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"Rejected answer"
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]
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}
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```
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@ -17,15 +17,15 @@
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其中 `prompt` 和 `response` 列应当是非空的字符串。`query` 列的内容将会和 `prompt` 列拼接作为模型输入。`history` 列应当是一个列表，其中每个元素是一个字符串二元组，分别代表用户请求和模型答复。
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对于奖励模型(rm)的数据集，头N个输出表示`chosen`的数据，后N个输出表示`rejected`的数据，例如：
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对于奖励模型或 DPO 训练的数据集，`response` 列应当是一个字符串列表，排在前面的代表更优的答案，例如：
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```json
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{
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"instruction": "Question?",
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"input": "",
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"output": [
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"chosen answer",
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"rejected answer"
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]
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"instruction": "Question",
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"input": "",
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"output": [
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"Chosen answer",
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"Rejected answer"
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]
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}
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```
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@ -589,3 +589,19 @@ register_template(
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"\n\n"
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]
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)
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r"""
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Supports: https://huggingface.co/xverse/XVERSE-13B-Chat
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"""
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register_template(
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name="xverse",
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prefix=[
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"{{system}}"
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],
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prompt=[
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"Human: {{query}}\n\nAssistant: "
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],
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system="",
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sep=[]
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)
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@ -21,7 +21,8 @@ class FinetuningArguments:
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Falcon choices: [\"32\", \"60\"], \
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Baichuan choices: [\"32\", \"40\"] \
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Qwen choices: [\"32\"], \
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XVERSE choices: [\"40\"]"}
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XVERSE choices: [\"40\"], \
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ChatGLM2 choices: [\"28\"]"}
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)
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num_layer_trainable: Optional[int] = field(
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default=3,
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@ -31,7 +32,7 @@ class FinetuningArguments:
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default="mlp",
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metadata={"help": "Name of trainable modules for partial-parameter (freeze) fine-tuning. \
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LLaMA choices: [\"mlp\", \"self_attn\"], \
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BLOOM & Falcon choices: [\"mlp\", \"self_attention\"], \
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BLOOM & Falcon & ChatGLM2 choices: [\"mlp\", \"self_attention\"], \
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Baichuan choices: [\"mlp\", \"self_attn\"], \
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Qwen choices: [\"mlp\", \"attn\"], \
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LLaMA-2, InternLM, XVERSE choices: the same as LLaMA."}
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@ -52,7 +53,7 @@ class FinetuningArguments:
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default=None,
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metadata={"help": "Name(s) of target modules to apply LoRA. Use commas to separate multiple modules. \
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LLaMA choices: [\"q_proj\", \"k_proj\", \"v_proj\", \"o_proj\", \"gate_proj\", \"up_proj\", \"down_proj\"], \
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BLOOM & Falcon choices: [\"query_key_value\", \"self_attention.dense\", \"mlp.dense\"], \
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BLOOM & Falcon & ChatGLM2 choices: [\"query_key_value\", \"self_attention.dense\", \"mlp.dense\"], \
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Baichuan choices: [\"W_pack\", \"o_proj\", \"gate_proj\", \"up_proj\", \"down_proj\"], \
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Qwen choices: [\"c_attn\", \"attn.c_proj\", \"w1\", \"w2\", \"mlp.c_proj\"], \
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LLaMA-2, InternLM, XVERSE choices: the same as LLaMA."}
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