Instructions to use pragy10/some_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pragy10/some_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pragy10/some_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pragy10/some_model") model = AutoModelForSequenceClassification.from_pretrained("pragy10/some_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from pragy10/some_model: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/pragy10/some_model/resolve/main/training_args.bin
- Command line
-
hf download hf://pragy10/some_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/pragy10/some_model/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- fb0a73befd1d7f3ae6af5421bdc37cbf26b0674fff36a99196963b306d03a07b
- Size of remote file:
- 5.18 kB
- SHA256:
- 5002f203f6faaf5de89185a5f44b948436141f64d88b023d361368e636b61e19
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