Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
Urdu
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use mahwizzzz/UrduClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mahwizzzz/UrduClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mahwizzzz/UrduClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mahwizzzz/UrduClassification") model = AutoModelForSequenceClassification.from_pretrained("mahwizzzz/UrduClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mahwizzzz/UrduClassification: direct link, hf CLI and curl.
- Browser
- Download file 504 MB
-
https://huggingface.co/mahwizzzz/UrduClassification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mahwizzzz/UrduClassification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mahwizzzz/UrduClassification/resolve/main/pytorch_model.bin
504 MB
- Xet hash:
- f42ae39acb2e5e587110763d420872c74229a3891887176873b01ac2635c2342
- Size of remote file:
- 504 MB
- SHA256:
- 3b651b749d2c2698b8a7dc957cb486baeecb8ff1bde121b06ee8e29cf4616d74
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.