Model: kojima-lab/molcrawl-molecule-nat-lang-mol-instructions-gpt2-small Source: Original Platform
72 lines
2.1 KiB
Markdown
72 lines
2.1 KiB
Markdown
---
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license: apache-2.0
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tags:
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- pytorch
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- gpt2
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- molecule-nl
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pipeline_tag: text-generation
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---
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# molcrawl-molecule-nat-lang-mol-instructions-gpt2-small
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## Model Description
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GPT-2 small (124M parameters) fine-tuned on molecule-oriented instruction data from [Mol-Instructions](https://huggingface.co/datasets/zjunlp/Mol-Instructions), starting from the `molcrawl-molecule-nat-lang-gpt2-small` pre-trained model.
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## Datasets
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- **Mol-Instructions**: [https://huggingface.co/datasets/zjunlp/Mol-Instructions](https://huggingface.co/datasets/zjunlp/Mol-Instructions) (Fine-tuning dataset)
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- **Model Type**: gpt2
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- **Data Type**: Molecule-NL
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- **Training Date**: 2026-04-24
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## Usage
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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model = AutoModelForCausalLM.from_pretrained("kojima-lab/molcrawl-molecule-nat-lang-mol-instructions-gpt2-small")
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tokenizer = AutoTokenizer.from_pretrained("kojima-lab/molcrawl-molecule-nat-lang-mol-instructions-gpt2-small")
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# Generate molecule-related text
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prompt = "The compound with SMILES CC(=O)Oc1ccccc1C(=O)O represents aspirin, which"
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inputs = tokenizer(prompt, return_tensors="pt")
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with torch.no_grad():
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output_ids = model.generate(
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**inputs,
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max_new_tokens=100,
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do_sample=True,
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temperature=0.8,
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eos_token_id=None, # HF config.json has legacy eos_token_id=0; disable early stop
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pad_token_id=0,
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)
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print(tokenizer.decode(output_ids[0], skip_special_tokens=True))
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```
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## Source Code
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Training pipeline, configuration files, and data preparation scripts are
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available in the MolCrawl GitHub repository:
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[https://github.com/mmai-framework-lab/MolCrawl](https://github.com/mmai-framework-lab/MolCrawl)
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## License
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This model is released under the APACHE-2.0 license.
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## Citation
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If you use this model, please cite:
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```bibtex
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@misc{molcrawl_molecule_nat_lang_mol_instructions_gpt2_small,
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title={molcrawl-molecule-nat-lang-mol-instructions-gpt2-small},
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author={{RIKEN}},
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year={2026},
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publisher={{Hugging Face}},
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url={{https://huggingface.co/kojima-lab/molcrawl-molecule-nat-lang-mol-instructions-gpt2-small}}
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}
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```
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