Text Classification
Transformers
PyTorch
Safetensors
English
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use badalsahani/pdf-classification-multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use badalsahani/pdf-classification-multi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="badalsahani/pdf-classification-multi")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("badalsahani/pdf-classification-multi") model = AutoModelForSequenceClassification.from_pretrained("badalsahani/pdf-classification-multi") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 73ed3ca0af4aeeac6bfcf45d047a4d3430880c93ac8bfdb17fc327a26b4d9081
- Size of remote file:
- 1.33 GB
- SHA256:
- 6d21efbaacb932f1de09c35c9ec917c7250ba27368155f49a9f6e6d5a5692b7a
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