This repo contains a fully fine-tuned LLaMA-7b, trained on the 🥼 biomolecule text instructions from the 🧪 Mol-Instructions dataset.

Instructions for running it can be found at https://github.com/zjunlp/Mol-Instructions.

Please refer to our paper for more details.

👁 image.png

🥼 Tasks

📝 Demo

As illustrated in our repository, we provide an example to perform generation.

>> python generate.py \
 --CLI True \
 --protein False\
 --load_8bit \
 --base_model $BASE_MODEL_PATH \
 --lora_weights $FINETUNED_MODEL_PATH \

Please download llama-7b-hf to obtain the pre-training weights of LLaMA-7B, refine the --base_model to point towards the location where the model weights are saved.

For model fine-tuned on biomolecular text instructions, set $FINETUNED_MODEL_PATH to 'zjunlp/llama-molinst-biotext-7b'.

🚨 Limitations

The current state of the model, obtained via instruction tuning, is a preliminary demonstration. Its capacity to handle real-world, production-grade tasks remains limited.

📚 References

If you use our repository, please cite the following related paper:

@inproceedings{fang2023mol,
 author = {Yin Fang and
 Xiaozhuan Liang and
 Ningyu Zhang and
 Kangwei Liu and
 Rui Huang and
 Zhuo Chen and
 Xiaohui Fan and
 Huajun Chen},
 title = {Mol-Instructions: {A} Large-Scale Biomolecular Instruction Dataset
 for Large Language Models},
 booktitle = {{ICLR}},
 publisher = {OpenReview.net},
 year = {2024},
 url = {https://openreview.net/pdf?id=Tlsdsb6l9n}
}

🫱🏻‍🫲 Acknowledgements

We appreciate LLaMA, Huggingface Transformers Llama, Alpaca, Alpaca-LoRA, Chatbot Service and many other related works for their open-source contributions.

Data and models for Mol-Instructions. • 9 items • Updated Jul 21, 2025 • 3