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
update link to im-lambda
Browse files
README.md
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| [ImmunoMatch](https://huggingface.co/fraternalilab/immunomatch) | A mixture of antibodies with both 魏 and 位 light chains |
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| [ImmunoMatch-魏](https://huggingface.co/fraternalilab/immunomatch-kappa) | Antibodies with 魏 light chains |
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| [ImmunoMatch-位](https://huggingface.co/fraternalilab/
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| [ImmunoMatch](https://huggingface.co/fraternalilab/immunomatch) | A mixture of antibodies with both 魏 and 位 light chains |
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| [ImmunoMatch-魏](https://huggingface.co/fraternalilab/immunomatch-kappa) | Antibodies with 魏 light chains |
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| [ImmunoMatch-位](https://huggingface.co/fraternalilab/immunomatch-lambda) | Antibodies with 位 light chains |
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