Instructions to use entropy/roberta_zinc_480m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use entropy/roberta_zinc_480m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="entropy/roberta_zinc_480m")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("entropy/roberta_zinc_480m") model = AutoModelForMaskedLM.from_pretrained("entropy/roberta_zinc_480m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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# Roberta Zinc 480m
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This is a Roberta style masked language model trained on ~480m SMILES strings from the [ZINC database](https://zinc.docking.org/).
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tags:
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- chemistry
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---
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# Roberta Zinc 480m
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This is a Roberta style masked language model trained on ~480m SMILES strings from the [ZINC database](https://zinc.docking.org/).
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