Instructions to use mljn/mdeberta-v3-base-finetuned-policy-statement-detection-token-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mljn/mdeberta-v3-base-finetuned-policy-statement-detection-token-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mljn/mdeberta-v3-base-finetuned-policy-statement-detection-token-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mljn/mdeberta-v3-base-finetuned-policy-statement-detection-token-classification") model = AutoModelForTokenClassification.from_pretrained("mljn/mdeberta-v3-base-finetuned-policy-statement-detection-token-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d1a15bfd51970ac01e66db1020f1386afeef89c11823665c10a2bba36485cf3d
- Size of remote file:
- 16 MB
- SHA256:
- 89ee6ed21d345eba7ad360473bde026240d8cf42fc67723b61162d9605784efa
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