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 optimizer.pt from prakhar2112/sectionHeaderBest: direct link, hf CLI and curl.
- Browser
- Download file 867 MB
-
https://huggingface.co/prakhar2112/sectionHeaderBest/resolve/main/optimizer.pt
- Command line
-
hf download hf://prakhar2112/sectionHeaderBest/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/prakhar2112/sectionHeaderBest/resolve/main/optimizer.pt
867 MB
- Xet hash:
- 36a310d6d4e010c6bce3961f2651957a203c5bcea866ed978b67c5ef6fc98779
- Size of remote file:
- 867 MB
- SHA256:
- 16a88210e104ce9679e16a14cccb8e40f5d91f64c25690552976f27aa3b1bfb0
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