Instructions to use CH3COOK/bert-base-embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CH3COOK/bert-base-embedding with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="CH3COOK/bert-base-embedding")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("CH3COOK/bert-base-embedding") model = AutoModelForMaskedLM.from_pretrained("CH3COOK/bert-base-embedding") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 590d4e27223f6715fb9f486d2820d686a3d64e2ae87d7a2606e0883815fff5f1
- Size of remote file:
- 440 MB
- SHA256:
- 335dc7be9f644ddc21c511563fe0bce4fd7d0c314f235fa6f0a95e8ef946c204
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