Unverified Commit d285bbd3 authored by echo840's avatar echo840 Committed by GitHub
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Update README.md

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...@@ -150,7 +150,7 @@ The json file used for Monkey training can be downloaded at [Link](https://drive ...@@ -150,7 +150,7 @@ The json file used for Monkey training can be downloaded at [Link](https://drive
**ATTENTION:** Specify the path to your training data, which should be a json file consisting of a list of conversations. **ATTENTION:** Specify the path to your training data, which should be a json file consisting of a list of conversations.
Inspired by Qwen-VL, we freeze the Large Language Model (LLM) and introduce LoRA into four linear layers ```"c_attn", "attn.c_proj", "w1", "w2"``` for training. This step makes it possible to train Monkey using 8 NVIDIA 3090 GPUs. The specific implementation code is in ```model_qwen_nvdia3090.py```. Inspired by Qwen-VL, we freeze the Large Language Model (LLM) and introduce LoRA into four linear layers ```"c_attn", "attn.c_proj", "w1", "w2"``` for training. This step makes it possible to train Monkey using 8 NVIDIA 3090 GPUs. The specific implementation code is in ```modeling_qwen_nvdia3090.py```.
- Add LoRA: You need to replace the contents of ```modeling_qwen.py``` with the contents of ```modeling_qwen_nvdia3090.py```. - Add LoRA: You need to replace the contents of ```modeling_qwen.py``` with the contents of ```modeling_qwen_nvdia3090.py```.
- Freeze LLM: You need to freeze other modules except LoRA and Resampler modules in ```finetune_multitask.py```. - Freeze LLM: You need to freeze other modules except LoRA and Resampler modules in ```finetune_multitask.py```.
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