Conversation with agent with finetuned model #240
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…d local hugging face model and finetune loaded model with hugging face dataset Added features to download models from hugging face model hub/load local hugging face model and finetune loaded model with hugging face dataset. Model loading and fine-tuning can happen both at the initialization stage and after the agent has been initialized (see README in `agentscope/examples/load_finetune_huggingface_model` for details). Major changes to the repo include creating the example script `load_finetune_huggingface_model`, adding a new model wrapper `HuggingFaceWrapper`, and creating a new agent type Finetune_DialogAgent. All changes are done in a new example directory `agentscope/examples/load_finetune_huggingface_model`.
made customized hyperparameters specification available from `model_configs` for fine-tuning at initialization, or through `fine_tune_config` in `Finetune_DialogAgent`'s `fine_tune` method after initialization
fixed issue related to `format` method
updated the dependencies needed
Updated the way to read token from .env file, so that it can work in any example directory.
ZiTao-Li
reviewed
May 22, 2024
rayrayraykk
reviewed
May 22, 2024
4 tasks
pan-x-c
reviewed
May 24, 2024
examples/conversation_with_agent_with_finetuned_model/finetune_dialogagent.py
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optimized the behavior of `device_map` when loading a huggingface model. Now if `device` is not given by the user, `device_map="auto"` by default; otherwise `device_map` is set to the user-specified `device`.
now the user can choose to do full-parameter finetuning by not passing `lora_config`
now the user can choose to do full-parameter finetuning by not passing `lora_config` and `bnb_config`
…etuned_model' into conversation_with_agent_with_finetuned_model
DavdGao
reviewed
Jun 21, 2024
examples/conversation_with_agent_with_finetuned_model/huggingface_model.py
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examples/conversation_with_agent_with_finetuned_model/huggingface_model.py
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examples/conversation_with_agent_with_finetuned_model/huggingface_model.py
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| Features include model and tokenizer loading, | ||
| and fine-tuning on the lima dataset with adjustable parameters. | ||
| """ | ||
| # pylint: disable=unused-import |
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If I remove it, there will be error 'W0611: Unused HuggingFaceWrapper imported from huggingface_model (unused-import)' when running pre-commit; furthermore, removing from huggingface_model import HuggingFaceWrapper will cause the default model wrapper being used and lead to error. Move HuggingFaceWrapper to agentscope/src/agentscope/models might solve this issue though.
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Can I proceed to make HuggingFaceWrapper part of agentscope/src/agentscope/models to resolve this issue?
| output_texts.append(text) | ||
| return output_texts | ||
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| def fine_tune_training( |
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Prefix the function that not exposed to users with "_"
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Done. But I didn't prefix format with an underscore as this is the case for all wrappers under agentscope/src/agentscope/models. Is format intended to be exposed to the users?
updated according to the latest comments
…ug for continual finetuning.
… `PeftModel` before convert it to `PeftModel`
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name: Pull Request
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Description
moved
conversation_with_agent_with_finetuned_modelto a separate branch from main to keep it consistent with the official repoChecklist
Please check the following items before code is ready to be reviewed.