Instructions to use Mahmoud8/small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mahmoud8/small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mahmoud8/small")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mahmoud8/small") model = AutoModelForSequenceClassification.from_pretrained("Mahmoud8/small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Mahmoud8/small: direct link, hf CLI and curl.
- Browser
- Download file 465 MB
-
https://huggingface.co/Mahmoud8/small/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Mahmoud8/small/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Mahmoud8/small/resolve/main/pytorch_model.bin
465 MB
- Xet hash:
- 0743537ef80592d873e69c6227afc7830a33dbaf753bb3d12c85f1d352f2c2ba
- Size of remote file:
- 465 MB
- SHA256:
- 27ed69ba5b65d10297c8e9cf2161f36630410433a6ecc8d68969c8c3fed453c1
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