Update README.md

README.md

@@ -10,8 +10,9 @@ license: apache-2.0
 ---
 
 # uqer1244/MLX-z-image
+https://github.com/uqer1244/MLX_z-image
 
-This is a **4-bit quantized MLX version** of [Tongyi-MAI/Z-Image-Turbo](https://huggingface.co/Tongyi-MAI/Z-Image-Turbo).
+This is a **4-bit quantized MLX version** of [{args.original_repo_id}](https://huggingface.co/{args.original_repo_id}).
 It is optimized for Apple Silicon (macOS) using the [MLX framework](https://github.com/ml-explore/mlx).
 
 ## Model Details
@@ -19,13 +20,13 @@ It is optimized for Apple Silicon (macOS) using the [MLX framework](https://gith
 - **Text Encoder**: MLX 4-bit quantized (Qwen3)
 - **VAE**: Original PyTorch Model (Sourced from original repo)
 - **Tokenizer**: Original Qwen2 Tokenizer (Sourced from original repo)
-- **Scheduler**: FlowMatchEulerDiscreteScheduler (Sourced from original repo)
+- **Scheduler**: MLXFlowMatchEulerScheduler
 
 ## Usage
 This model can be used with the custom MLX pipeline script.
 Please refer to the original repository for detailed usage instructions regarding the model architecture.
 
 ## Attribution & License
-This model is a derivative work of [Tongyi-MAI/Z-Image-Turbo](https://huggingface.co/Tongyi-MAI/Z-Image-Turbo).
+This model is a derivative work of [{args.original_repo_id}](https://huggingface.co/{args.original_repo_id}).
 - **Original License**: Apache 2.0
-- **Modifications**: Converted Transformer and Text Encoder weights to MLX format and quantized to 4-bit.
+- **Modifications**: Converted Transformer and Text Encoder weights to MLX format and quantized to 4-bit.