Yin Fang
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README.md
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---
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license: apache-2.0
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---
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---
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license: apache-2.0
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tags:
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- chemistry
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- biology
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- molecule
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- instructions
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---
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This repo contains a low-rank adapter for [LLaMA-7b](https://huggingface.co/decapoda-research/llama-7b-hf), trained on the 🔬 **molecule-oriented instructions** from the 🧪 [Mol-Instructions](https://huggingface.co/datasets/zjunlp/Mol-Instructions) dataset.
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Instructions for running it can be found at https://github.com/zjunlp/Mol-Instructions.
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> Please refer to our [paper](https://arxiv.org/abs/2306.08018) for more details.
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<h3> 🔬 Tasks</h3>
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<details>
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<summary><b>Molecule description generation</b></summary>
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- *Please give me some details about this molecule:*
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[C][C][C][C][C][C][C][C][C][C][C][C][C][C][C][C][C][C][=Branch1][C][=O][O][C@H1][Branch2][Ring1][=Branch1][C][O][C][=Branch1][C][=O][C][C][C][C][C][C][C][C][C][C][C][C][C][C][C][C][O][P][=Branch1][C][=O][Branch1][C][O][O][C][C@@H1][Branch1][=Branch1][C][=Branch1][C][=O][O][N]
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```
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The molecule is a 3-sn-phosphatidyl-L-serine in which the phosphatidyl acyl groups at positions 1 and 2 are specified as stearoyl and arachidonoyl respectively.
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It is functionally related to an arachidonic acid and an octadecanoic acid.
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```
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</details>
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<details>
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<summary><b>Description-guided molecule design</b></summary>
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- *Create a molecule with the structure as the one described:*
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The molecule is a primary arylamine in which an amino functional group is substituted for one of the benzene hydrogens. It is a primary arylamine and a member of anilines.
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```
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[N][C][=C][C][=C][C][=C][Ring1][=Branch1]
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```
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</details>
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<details>
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<summary><b>Forward reaction prediction</b></summary>
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- *With the provided reactants and reagents, propose a potential product:*
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[O][=N+1][Branch1][C][O-1][C][=C][N][=C][Branch1][C][Cl][C][Branch1][C][I][=C][Ring1][Branch2].[Fe]
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```
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[N][C][=C][N][=C][Branch1][C][Cl][C][Branch1][C][I][=C][Ring1][Branch2]
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```
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</details>
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<details>
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<summary><b>Retrosynthesis</b></summary>
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- *Please suggest potential reactants used in the synthesis of the provided product:*
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[C][=C][C][C][N][C][=Branch1][C][=O][O][C][Branch1][C][C][Branch1][C][C][C]
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```
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[C][=C][C][C][N].[C][C][Branch1][C][C][Branch1][C][C][O][C][=Branch1][C][=O][O][C][=Branch1][C][=O][O][C][Branch1][C][C][Branch1][C][C][C]
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```
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</details>
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<details>
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<summary><b>Reagent prediction</b></summary>
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- *Please provide possible reagents based on the following chemical reaction:*
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[C][C][=C][C][=C][Branch1][C][N][C][=N][Ring1][#Branch1].[O][=C][Branch1][C][Cl][C][Cl]>>[C][C][=C][C][=C][Branch1][Branch2][N][C][=Branch1][C][=O][C][Cl][C][=N][Ring1][O]
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```
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[C][C][C][O][C][Ring1][Branch1].[C][C][N][Branch1][Ring1][C][C][C][C].[O]
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```
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</details>
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<details>
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<summary><b>Property prediction</b></summary>
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- *Please provide the HOMO energy value for this molecule:*
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[C][C][O][C][C][Branch1][C][C][C][Branch1][C][C][C]
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```
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-0.2482
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```
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</details>
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<h3> 📝 Demo</h3>
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As illustrated in [our repository](https://github.com/zjunlp/Mol-Instructions/tree/main/demo), we provide an example to perform generation.
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```shell
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>> python generate.py \
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--CLI True \
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--protein False\
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--load_8bit \
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--base_model $BASE_MODEL_PATH \
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--lora_weights $FINETUNED_MODEL_PATH \
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```
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Please download [llama-7b-hf](https://huggingface.co/decapoda-research/llama-7b-hf/tree/main) to obtain the pre-training weights of LLaMA-7B, refine the `--base_model` to point towards the location where the model weights are saved.
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For model fine-tuned on **molecule-oriented** instructions, set `$FINETUNED_MODEL_PATH` to `'zjunlp/llama-molinst-molecule-7b'`.
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<h3> 🚨 Limitations</h3>
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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.
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<h3> 📚 References</h3>
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If you use our repository, please cite the following related paper:
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```
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@article{molinst,
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title={Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models},
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author={Fang, Yin and Liang, Xiaozhuan and Zhang, Ningyu and Liu, Kangwei and Huang, Rui and Chen, Zhuo and Fan, Xiaohui and Chen, Huajun},
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journal={arXiv preprint arXiv:2306.08018},
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year={2023}
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}
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```
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<h3> 🫱🏻🫲🏾 Acknowledgements</h3>
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We appreciate [LLaMA](https://github.com/facebookresearch/llama), [Huggingface Transformers Llama](https://github.com/huggingface/transformers/tree/main/src/transformers/models/llama), [Alpaca](https://crfm.stanford.edu/2023/03/13/alpaca.html), [Alpaca-LoRA](https://github.com/tloen/alpaca-lora), [Chatbot Service](https://github.com/deep-diver/LLM-As-Chatbot) and many other related works for their open-source contributions.
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