Instructions to use leetdavid/relevance-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leetdavid/relevance-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="leetdavid/relevance-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("leetdavid/relevance-model") model = AutoModelForSequenceClassification.from_pretrained("leetdavid/relevance-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Librarian Bot: Add base_model information to model (#1)
- Librarian Bot: Add base_model information to model (4bab2c73de41d8eb6defb144259bb9b520823c5b) Co-authored-by: Librarian Bot (Bot) <librarian-bot@users.noreply.huggingface.co>7b88dbb
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add model
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initial commit
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