Feature Extraction
Transformers
Safetensors
prism
video
representation-learning
view-invariant
cross-view
egocentric
egoexo4d
emnlp2026
custom_code
Instructions to use litcoderr/prism with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use litcoderr/prism with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="litcoderr/prism", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("litcoderr/prism", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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MIT licensed. The frozen backbones keep their own licenses.
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[paper]:
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[project]: https://github.
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[code]: https://github.com/litcoderr/prism
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MIT licensed. The frozen backbones keep their own licenses.
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[paper]: arxiv.org/abs/2608.30388
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[project]: https://litcoderr.github.io/prism_page/
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[code]: https://github.com/litcoderr/prism
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