Instructions to use jayantigoyal/docintel-extractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jayantigoyal/docintel-extractor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="jayantigoyal/docintel-extractor")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("jayantigoyal/docintel-extractor") model = AutoModelForTokenClassification.from_pretrained("jayantigoyal/docintel-extractor") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e5d75276ff205ad7288279211a14e73bef0c056af4b6a3c73a434d5fa17f9bf4
- Size of remote file:
- 5.27 kB
- SHA256:
- c511eda95233197ae6603412aa8faf10c07da8eac3f4f3f1815bfb1cb3a5956f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.