Instructions to use LeCastre/DistilBert-pMHC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LeCastre/DistilBert-pMHC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LeCastre/DistilBert-pMHC")# Load model directly from transformers import AutoTokenizer, BertRnnDist tokenizer = AutoTokenizer.from_pretrained("LeCastre/DistilBert-pMHC") model = BertRnnDist.from_pretrained("LeCastre/DistilBert-pMHC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c0ec0aa6dc4819ba6e527c01d191a662f904321b7dfa400d1ef164beb083a082
- Size of remote file:
- 362 MB
- SHA256:
- 0e12f5523fad379f3d8daf2a5b1246b04447af094a5b12674becf9e306854cff
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