Instructions to use wukevin/tcr-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wukevin/tcr-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wukevin/tcr-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wukevin/tcr-bert") model = AutoModelForSequenceClassification.from_pretrained("wukevin/tcr-bert") - Inference
- Notebooks
- Google Colab
- Kaggle
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README.md
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- Masked language modeling
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- Classification across antigen labels from PIRD
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Example
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- Masked language modeling
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- Classification across antigen labels from PIRD
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Example inputs:
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* `C A S S P V T G G I Y G Y T F` (binds to NLVPMVATV CMV antigen)
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* `C A T S G R A G V E Q F F` (binds to GILGFVFTL flu antigen)
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