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:
- 1194f562dfa80dd14f9cbcf715eb1c99d15ed780491e04f016f1e94001ff01d5
- Size of remote file:
- 440 MB
- SHA256:
- 2cf83467799040bad74bc71b81d3fe2bfbe06b166ca2d21b3cfc784124b27b18
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