Instructions to use clairedhx/camenBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use clairedhx/camenBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="clairedhx/camenBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("clairedhx/camenBERT") model = AutoModelForTokenClassification.from_pretrained("clairedhx/camenBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0b1cdc634d0f493996ecc4d3d2d9be936ba25d389c4089a1f6bf995adf3e9af8
- Size of remote file:
- 440 MB
- SHA256:
- 31fc6e6f9957e269c0cc5ffd11b9b596f8ec2fb47eefa88f12cca89ea147fd8f
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