Instructions to use Gnanesh5/SF5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gnanesh5/SF5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Gnanesh5/SF5")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Gnanesh5/SF5") model = AutoModelForSequenceClassification.from_pretrained("Gnanesh5/SF5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Gnanesh5/SF5: direct link, hf CLI and curl.
- Browser
- Download file 469 MB
-
https://huggingface.co/Gnanesh5/SF5/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Gnanesh5/SF5/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Gnanesh5/SF5/resolve/main/pytorch_model.bin
469 MB
- Xet hash:
- 27c12bad4c0ae3fc8dee6b378e6d3770d55dfc978eb5ab8255b49066cd0f635d
- Size of remote file:
- 469 MB
- SHA256:
- d0fdce81b63bc33741055824bb7f319ff2c87f2594aa51948f30c8f65471aa01
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