Instructions to use fraternalilab/immunomatch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fraternalilab/immunomatch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fraternalilab/immunomatch")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fraternalilab/immunomatch") model = AutoModelForSequenceClassification.from_pretrained("fraternalilab/immunomatch") - Notebooks
- Google Colab
- Kaggle
innit the readme
Browse files
README.md
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- accuracy
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tags:
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- biology
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---
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ImmunoMatch is a protein language model finetuned from AntiBERTa2, aiming at investigating the heavy and light chain pairing preferences in antibody.
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- accuracy
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tags:
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- biology
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base_model:
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- alchemab/antiberta2-cssp
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---
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ImmunoMatch is a protein language model finetuned from AntiBERTa2, aiming at investigating the heavy and light chain pairing preferences in antibody.
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