Instructions to use fbaigt/procbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fbaigt/procbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="fbaigt/procbert")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("fbaigt/procbert") model = AutoModel.from_pretrained("fbaigt/procbert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 892e74af44cdd099183a96a39b7a2ff1c115a83b997a4c3ec6fc820e784ecdfa
- Size of remote file:
- 436 MB
- SHA256:
- f442430154faaf95b81ab6d4bf5589448c8964a8eeef465ef72500b6be4a0c8a
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