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--- |
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license: unknown |
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base_model: |
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- lllyasviel/FramePackI2V_HY |
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--- |
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## Model Details |
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This model card is for mxfp8 quantization of [lllyasviel/FramePackI2V_HY](https://huggingface.co/lllyasviel/FramePackI2V_HY) based on [intel/auto-round](https://github.com/intel/auto-round). |
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The model is not able to be published due to license limitation. Please follow the INC example README to generate and evaluate the low precision models. |
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## How to Use |
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The step-by-step README of quantization and evaluation can be found in [Intel Neural Compressor Examples](https://github.com/intel/neural-compressor/blob/master/examples/pytorch/diffusion_model/diffusers/framepack/README.md). |
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## Evaluate Results |
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| Task | backend | BF16 | MXFP8 | |
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|:-------------------:|:-------:|:------:|:------:| |
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| subject_consistency | vllm | 0.9656 | 0.9656 | |
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| i2v_background | vllm | 0.9928 | 0.9936 | |
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| dynamic_degree | vllm | 0.2724 | 0.2724 | |
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| imaging_quality | vllm | 0.7036 | 0.7018 | |
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## Ethical Considerations and Limitations |
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The model can produce factually incorrect output, and should not be relied on to produce factually accurate information. |
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Because of the limitations of the pretrained model and the finetuning datasets, it is possible that this model could generate lewd, biased or otherwise offensive outputs. |
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Therefore, before deploying any applications of the model, developers should perform safety testing. |
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## Caveats and Recommendations |
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. |
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Here are a couple of useful links to learn more about Intel's AI software: |
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- [Intel Neural Compressor](https://github.com/intel/neural-compressor) |
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- [AutoRound](https://github.com/intel/auto-round) |
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## Disclaimer |
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The license on this model does not constitute legal advice. |
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We are not responsible for the actions of third parties who use this model. |
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Please consult an attorney before using this model for commercial purposes. |