Feature Extraction
Transformers
Safetensors
gpt2
safe
datamol-io
molecule-design
smiles
Generated from Trainer
Instructions to use anrilombard/safe-100m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anrilombard/safe-100m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="anrilombard/safe-100m")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("anrilombard/safe-100m") model = AutoModel.from_pretrained("anrilombard/safe-100m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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## References
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```bibtex
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@article{noutahi2024gotta,
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title={Gotta be SAFE: a new framework for molecular design},
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## References
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```bibtex
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@inproceedings{
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lombard2024molecular,
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title={Molecular Generation with State Space Sequence Models},
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author={Anri Lombard and Shane Acton and Ulrich Armel Mbou Sob and Jan Buys},
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booktitle={NeurIPS 2024 Workshop on AI for New Drug Modalities},
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year={2024},
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url={https://openreview.net/forum?id=1ib5oyTQIb}
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}
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```
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```bibtex
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@article{noutahi2024gotta,
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title={Gotta be SAFE: a new framework for molecular design},
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