Instructions to use BMILab/TCR-BERT-PositionLoss with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BMILab/TCR-BERT-PositionLoss with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BMILab/TCR-BERT-PositionLoss")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BMILab/TCR-BERT-PositionLoss") model = AutoModelForMaskedLM.from_pretrained("BMILab/TCR-BERT-PositionLoss") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:f60ca9132269624232b0c168426ac303ee5d477145e12420f61df59e1c7aadbf
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size 229576452
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