Instructions to use iamroot/zero-shot-embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iamroot/zero-shot-embedding with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="iamroot/zero-shot-embedding", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("iamroot/zero-shot-embedding", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f52b79311d8c87c4911e68ff149786730a3431a07ec45e71e511280dd4cc7181
- Size of remote file:
- 13.6 MB
- SHA256:
- 5998feff9e1e33676387508acb83f692e03e5f5abec745c346a629e177127f85
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