Instructions to use namednil/STEP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use namednil/STEP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="namednil/STEP", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("namednil/STEP", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8dc9a62fd096c4b831de1044d7f79e02f0a22e9d8fb5699f0cfa8d83a1f8fc9d
- Size of remote file:
- 953 MB
- SHA256:
- 81b4cb710ab07381fec17e6e356da27ddd6a000b1bfe2d3e85bb9f99dfc8654a
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