Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use mahwizzzz/RomanUrduClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mahwizzzz/RomanUrduClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mahwizzzz/RomanUrduClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mahwizzzz/RomanUrduClassification") model = AutoModelForSequenceClassification.from_pretrained("mahwizzzz/RomanUrduClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from mahwizzzz/RomanUrduClassification: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/mahwizzzz/RomanUrduClassification/resolve/main/training_args.bin
- Command line
-
hf download hf://mahwizzzz/RomanUrduClassification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/mahwizzzz/RomanUrduClassification/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- b8030b015c8b5da93fd5bf4d39a67333a2118a44a7ed98bbd6bd6a91029ad301
- Size of remote file:
- 3.96 kB
- SHA256:
- b2156a066b8ab016be16b13c77711d9e09905473e54d5ca61eec7618eab88955
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