DisCa

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tencent
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Quick Summary

AI model with specialized capabilities.

Code Examples

🛠 Installationtext
## 🪐 Experiments

### Text-to-Video (T2V) Task on HunyuanVideo-1.0
The experiments for the Text-to-Video task are conducted on **HunyuanVideo-1.0**. Given that the original project does not provide inference scripts for MeanFlow, we have supplemented them in this project. 

We provide two scripts to implement the proposed methods:
* `infer_r_meanflow.sh` for **Restricted MeanFlow**
* `infer_disca.sh` for **DisCa**

The environment setup follows the official HunyuanVideo-1.0 configuration. We have enabled command-line argument passing; you can modify these arguments directly within the bash files or execute them via the command line.

### Image-to-Video (I2V) Task on HunyuanVideo-1.5
The experiments for the Image-to-Video task are conducted on **HunyuanVideo-1.5**. Because HunyuanVideo-1.5 is already well-adapted for MeanFlow inference, this project provides a lightweight and concise codebase. 

Since the Image-to-Video task inherently possesses stronger control signals and is easier to distill, coupled with the enhanced capabilities of HunyuanVideo-1.5, the I2V implementation in this project achieves a higher compression ratio.

**Getting Started:**
1. Follow the instructions in [`disca_i2v_hyvideo15/README.md`](disca_i2v_hyvideo15/README.md) to quickly set up the environment and configure the code.
2. Execute the inference directly using `infer_disca.sh`.

**Restricted MeanFlow Component:**
For the corresponding Restricted MeanFlow component, you can use the [HunyuanVideo-1.5-480P-I2V-step-distill](https://huggingface.co/tencent/HunyuanVideo-1.5/tree/main/transformer/480p_i2v_step_distilled) model provided in the official HunyuanVideo-1.5 repository. This model is distilled using similar techniques and has undergone further optimization.


## 📚 Citation

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