Fill-Mask
Transformers
Safetensors
English
esmc
biology
esm
protein
protein-language-model
protein-embeddings
masked-language-modeling
transfer-learning
variant-effect-prediction
protein-engineering
Instructions to use biohub/ESMC-6B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use biohub/ESMC-6B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="biohub/ESMC-6B")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("biohub/ESMC-6B") model = AutoModelForMaskedLM.from_pretrained("biohub/ESMC-6B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
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## Performance Metrics
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![][fig2]
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Performance metrics are detailed in our [ESMC & ESMFold2 paper](https://biohub.ai/papers/esm_protein.pdf).
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## Usage
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- Should you have any security or privacy issues or questions related to the services, please reach out to our team at [support@biohub.org](mailto:support@biohub.org).
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[pal]: images/contact_pal.png
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[fig2]: images/esmc_graphic.png
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## Performance Metrics
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Performance metrics are detailed in our [ESMC & ESMFold2 paper](https://biohub.ai/papers/esm_protein.pdf).
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## Usage
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- Should you have any security or privacy issues or questions related to the services, please reach out to our team at [support@biohub.org](mailto:support@biohub.org).
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[pal]: images/contact_pal.png
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