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:
- 914aae3c208f295fc9110207a9158011564a27b962b9d4372767fd5e039e1f13
- Size of remote file:
- 436 MB
- SHA256:
- 01e38b4e341afc85d0bcf1de21cfa830112664746ee56197ac78dc7ce77d2f34
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