Instructions to use wandb/deberta-small-relevance with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wandb/deberta-small-relevance with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="wandb/deberta-small-relevance", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("wandb/deberta-small-relevance", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from wandb/deberta-small-relevance: direct link, hf CLI and curl.
- Browser
- Download file 8.65 MB
-
https://huggingface.co/wandb/deberta-small-relevance/resolve/main/tokenizer.json
- Command line
-
hf download hf://wandb/deberta-small-relevance/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/wandb/deberta-small-relevance/resolve/main/tokenizer.json
8.65 MB
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