Instructions to use raoulmago/doc_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raoulmago/doc_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="raoulmago/doc_classification")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("raoulmago/doc_classification") model = AutoModelForTokenClassification.from_pretrained("raoulmago/doc_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ae1bd20703b387d2e323d5b32a558631ffba7e910a2ec8657c4ea78e9e0b59f6
- Size of remote file:
- 4.6 kB
- SHA256:
- 3ecc64bde5115ddf3f4d1aeba19e5a79364ac2eec4de511fdd79a9571cedd605
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