Transformers
PyTorch
bart
text2text-generation
molecular language model
SELFIES
molecule optimization
Instructions to use zjunlp/MolGen-large-opt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zjunlp/MolGen-large-opt with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("zjunlp/MolGen-large-opt") model = AutoModelForSeq2SeqLM.from_pretrained("zjunlp/MolGen-large-opt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Yin Fang commited on
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@@ -47,15 +47,16 @@ Molecule optimization example:
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### BibTeX entry and citation info
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```bibtex
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@
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author = {Yin Fang and
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Ningyu Zhang and
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Zhuo Chen and
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Xiaohui Fan and
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Huajun Chen},
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title = {Domain-Agnostic Molecular Generation with Self-feedback},
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year = {
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}
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```
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### BibTeX entry and citation info
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```bibtex
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+
@inproceedings{fang2023domain,
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author = {Yin Fang and
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Ningyu Zhang and
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Zhuo Chen and
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Xiaohui Fan and
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Huajun Chen},
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title = {Domain-Agnostic Molecular Generation with Self-feedback},
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booktitle = {{ICLR}},
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publisher = {OpenReview.net},
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year = {2024},
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url = {https://openreview.net/pdf?id=9rPyHyjfwP}
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}
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```
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