Update README.md

README.md

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-# LatentSync on Hugging Face Spaces (T4 GPU)
-
-This is a working implementation of LatentSync 1.5 for lip-sync generation on Hugging Face Spaces with T4 GPU.
-
-## Key Fixes Applied
-
-1. **Config Path Fixed**: Changed from `configs/unet.yaml` to `configs/unet/stage2.yaml`
-2. **Requirements Optimized**: Properly formatted with newlines between packages
-3. **Python Version**: Using Python 3.10.13 as specified in `runtime.txt`
-
-## Files Required
-
-- `app.py` - Main application (UPDATED with correct config path)
-- `requirements.txt` - Python dependencies (UPDATED with proper formatting)
-- `packages.txt` - System packages (ffmpeg, git)
-- `runtime.txt` - Should contain: `python-3.10.13`
-
-## How It Works
-
-1. Clones LatentSync repository at runtime
-2. Downloads model checkpoints from `ByteDance/LatentSync-1.5`
-3. Converts input image + audio to a static video
-4. Runs lip-sync inference
-5. Returns the generated video
-
-## Model Notes
-
-- Using **LatentSync 1.5** which works better on T4 GPU (16GB)
-- Config: `configs/unet/stage2.yaml` (standard stage 2 config)
-- Alternative: For v1.6, use `configs/unet/stage2_512.yaml` and update `HF_CKPT_REPO` to `ByteDance/LatentSync-1.6`
-
-## Inference Parameters
-
-- **Inference Steps**: 10-40 (default 20)
-- **Guidance Scale**: 0.8-2.0 (default 1.0)
-- **Seed**: For reproducibility
-- **DeepCache**: Enabled by default for faster inference
-
-## GPU Requirements
-
-- T4 Small (16GB) - Works with LatentSync 1.5
-- Inference takes ~30-60 seconds per generation
-
-## Common Issues
-
-### If you get "FileNotFoundError: configs/unet.yaml"
-- Make sure you're using the updated `app.py` with the correct path: `configs/unet/stage2.yaml`
-
-### If you get CUDA out of memory
-- Reduce inference steps to 15
-- Make sure DeepCache is enabled
-- Use smaller input images (256x256 recommended)
-
-### If output quality is poor
-- Try increasing guidance_scale to 1.5-2.0
-- Increase inference_steps to 30-40
-- For v1.6, switch to `stage2_512.yaml` config for better quality
-
-## Credits
-
-Based on [LatentSync by ByteDance](https://github.com/bytedance/LatentSync)
+title: Model Testing
+emoji: 📉
+colorFrom: indigo
+colorTo: red
+sdk: gradio
+sdk_version: 6.5.1
+app_file: app.py
+pinned: false
+license: apache-2.0
+short_description: Space for testing new open source AI Avatar models