Instructions to use prakhar2112/sectionHeaderBest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prakhar2112/sectionHeaderBest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="prakhar2112/sectionHeaderBest")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("prakhar2112/sectionHeaderBest") model = AutoModelForSequenceClassification.from_pretrained("prakhar2112/sectionHeaderBest", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from prakhar2112/sectionHeaderBest: direct link, hf CLI and curl.
- Browser
- Download file 3.26 kB
-
https://huggingface.co/prakhar2112/sectionHeaderBest/resolve/main/training_args.bin
- Command line
-
hf download hf://prakhar2112/sectionHeaderBest/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/prakhar2112/sectionHeaderBest/resolve/main/training_args.bin
3.26 kB
- Xet hash:
- d6f8e7eccb34f31847a94308f952ce4e36bef4220c0b6e5f81c1f17988edfa3c
- Size of remote file:
- 3.26 kB
- SHA256:
- 9e9c70b6596a6d55f6c0bc7f9cbff92e177801478f724c02a1b55f1eeb752ea6
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