Add model card metadata and link to paper and project page

This PR adds a model card by linking it to the paper [REPA-E: Unlocking VAE for End-to-End Tuning of Latent Diffusion Transformers](https://huggingface.co/papers/2504.10483).

The PR improves the model card by adding the relevant `pipeline_tag` and `library_name`, ensuring people can find your model more easily on the Hub. It also adds a link to the project page.

Please review and merge this PR if everything looks good.

README.md

@@ -1,3 +1,39 @@
----
-license: mit
----
+---
+license: mit
+library_name: diffusers
+pipeline_tag: image-to-image
+---
+
+---
+license: mit
+library_name: diffusers
+pipeline_tag: image-to-image
+---
+
+# REPA-E: Unlocking VAE for End-to-End Tuning of Latent Diffusion Transformers
+
+This model implements the REPA-E approach for end-to-end tuning of latent diffusion transformers, as described in the paper [REPA-E: Unlocking VAE for End-to-End Tuning of Latent Diffusion Transformers](https://huggingface.co/papers/2504.10483). REPA-E enables stable and effective joint training of both the VAE and the diffusion model, leading to faster training and improved generation quality.
+
+For more information, please refer to the following resources:
+
+*   **Project Page:** https://end2end-diffusion.github.io
+*   **GitHub Repository:** https://github.com/REPA-E/REPA-E
+
+## Usage
+
+You can use this model with the `diffusers` library. Here's a basic example:
+
+```python
+from diffusers import DiffusionPipeline
+
+# Load the pipeline
+pipeline = DiffusionPipeline.from_pretrained("REPA-E/your-model-name") # Replace "REPA-E/your-model-name"
+
+# Generate an image
+image = pipeline().images[0]
+
+# Save the image
+image.save("generated_image.png")
+```
+
+Please refer to the GitHub repository for detailed instructions and more advanced usage examples.