Instructions to use prithivida/bert-for-patents-64d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivida/bert-for-patents-64d with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="prithivida/bert-for-patents-64d")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("prithivida/bert-for-patents-64d") model = AutoModel.from_pretrained("prithivida/bert-for-patents-64d") - Notebooks
- Google Colab
- Kaggle
Commit ·
a337ab9
1
Parent(s): 7be14dd
Add TF weights (#1)
Browse files- Add TF weights (d34069ea1903e160a6c425cf688175af9e760e79)
Co-authored-by: Joao Gante <joaogante@users.noreply.huggingface.co>
- tf_model.h5 +3 -0
tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:13d1d1e13882021b784db19e9d14a4acbe4ea5c70b67bb1779950fa7f1dbda5d
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size 1379326720
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