Instructions to use browndw/docusco-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use browndw/docusco-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="browndw/docusco-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("browndw/docusco-bert") model = AutoModelForTokenClassification.from_pretrained("browndw/docusco-bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d90d9d58568a11aa0576272c133f4e4b2b760a08c8288251ca26624a78ab3d3
- Size of remote file:
- 431 MB
- SHA256:
- 4e992dfab7211cf67dbab4d804eecb4c6518b48f5ffef702d7f3e7486032b805
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