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 training_args.bin from Gnanesh5/SF5: direct link, hf CLI and curl.
- Browser
- Download file 3.39 kB
-
https://huggingface.co/Gnanesh5/SF5/resolve/main/training_args.bin
- Command line
-
hf download hf://Gnanesh5/SF5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Gnanesh5/SF5/resolve/main/training_args.bin
3.39 kB
- Xet hash:
- 9f53b116d2ceb0c246fb4975d1098027c997aedc270b26e5f82d41705085033a
- Size of remote file:
- 3.39 kB
- SHA256:
- 27377ac63729d19d80318fa8ad44bbe609aab47dab92d980457513cf71b72cab
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