Instructions to use cuadron11/documentClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cuadron11/documentClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cuadron11/documentClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cuadron11/documentClassification") model = AutoModelForSequenceClassification.from_pretrained("cuadron11/documentClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a646ff4349a2353d5ce9aeb3b6d5e6dc79bc652c4d3dc91c665247e27dba150
- Size of remote file:
- 499 MB
- SHA256:
- f9217f91dca59c977e94ace6e31d0b8f3150e239ab6df97f511bb25d0fb2f8d2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.