Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Umesh/pulf-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Umesh/pulf-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Umesh/pulf-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Umesh/pulf-classifier") model = AutoModelForSequenceClassification.from_pretrained("Umesh/pulf-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Umesh/pulf-classifier: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Umesh/pulf-classifier/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://Umesh/pulf-classifier@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Umesh/pulf-classifier/resolve/refs%2Fpr%2F1/pytorch_model.bin
438 MB
- Xet hash:
- 9192b71f2677f289fd975742609f1c101aab91610bf60758c9a92c5b25c68838
- Size of remote file:
- 438 MB
- SHA256:
- 6c0776e6b1baf74e0ea8736bdc2ead6c2c407801c0e5b4d42a6235054f12ae25
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