Feature Extraction
Transformers
Safetensors
vila
omni-modal
multimodal
vision
audio
video
llm
custom_code
Eval Results (legacy)
Instructions to use nvidia/omnivinci with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/omnivinci with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="nvidia/omnivinci", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nvidia/omnivinci", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 211c2d969a7c23f2dfc315941cb329c945239456d88b8f0db5d468f9fe270328
- Size of remote file:
- 11.4 MB
- SHA256:
- 491635783283196cfd9ab5d019617234a246b35a58da4761afd6ad77380f43c8
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