Instructions to use BMILab/TCR-BERT-Substring with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BMILab/TCR-BERT-Substring with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BMILab/TCR-BERT-Substring")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BMILab/TCR-BERT-Substring") model = AutoModelForMaskedLM.from_pretrained("BMILab/TCR-BERT-Substring") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
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:b45467ae03641e9b732777d418d7b5054b95ef1db9cf9e44df6f87daa281602c
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size 1215711348
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