Other
Transformers
Safetensors
spearmint
feature-extraction
immunology
stability
pMHC
epitope
neoantigen
personalized_immunotherapy
custom_code
Instructions to use dkarthikeyan1/spearmint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dkarthikeyan1/spearmint with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dkarthikeyan1/spearmint", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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### Preprocessing
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Amino acids were standardized to fit the ESM-2 tokenizer. MHC allele information was standardized using
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[mhcgnomes](https://pypi.org/project/mhcgnomes/),
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the consensus HLA as found in [IMGT](https://www.ebi.ac.uk/ipd/imgt/hla/).
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### Pre-training
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### Preprocessing
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Amino acids were standardized to fit the ESM-2 tokenizer. MHC allele information was standardized using
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[mhcgnomes](https://pypi.org/project/mhcgnomes/), before mapping allele information to
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the consensus HLA as found in [IMGT](https://www.ebi.ac.uk/ipd/imgt/hla/).
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### Pre-training
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