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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81048fa202784abcfeb5f8a4a4273f3364d393d5b8b7337a2a517f497bcb0f63
- Size of remote file:
- 669 kB
- SHA256:
- ca505be6b19b59c080886f9c41db8971878f4876cb59cdf87aa30b34fee28d67
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