Instructions to use nvidia/Cosmos-0.1-Tokenizer-DI8x8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use nvidia/Cosmos-0.1-Tokenizer-DI8x8 with NeMo:
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- Notebooks
- Google Colab
- Kaggle
Add link to Cosmos Tokenizer README in NeMo repository
Browse files
README.md
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@@ -226,6 +226,9 @@ input_tensor = torch.randn(1, 3, 512, 512).to('cuda').to(torch.bfloat16)
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(indices, codes) = model.encode(input_tensor)
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```
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# Evaluation
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## TokenizationPerformance Comparison
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(indices, codes) = model.encode(input_tensor)
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```
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Please see the [Cosmos Tokenizer README within the NeMo repository](https://github.com/NVIDIA/NeMo/tree/main/nemo/collections/common/video_tokenizers) for additional examples to create training datasets with Cosmos Tokenizer.
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# Evaluation
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## TokenizationPerformance Comparison
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