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README.md

@@ -19,7 +19,7 @@ base_model:
 
 # FLUX.1-dev-ControlNet-Union-Pro-2.0 (fp8)
 
-This repository contains an unified ControlNet for FLUX.1-dev model released by [Shakker Labs](https://huggingface.co/Shakker-Labs). This version has been quantized to FP8 format for optimized inference performance. We provide an [online demo](https://huggingface.co/spaces/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro-2.0).
+This repository contains an unified ControlNet for FLUX.1-dev model released by [Shakker Labs](https://huggingface.co/Shakker-Labs). This is a direct quantization of the original model to FP8 format for optimized inference performance (not a fine-tuned version). We provide an [online demo](https://huggingface.co/spaces/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro-2.0).
 
 # FP8 Quantization
 This model has been quantized from the original BFloat16 format to FP8 format. The benefits include:
@@ -27,6 +27,8 @@ This model has been quantized from the original BFloat16 format to FP8 format. T
 - **Faster Inference**: Potential speed improvements, especially on hardware with FP8 support
 - **Minimal Quality Loss**: Carefully calibrated quantization process to preserve output quality
 
+Note: This is a direct quantization of [Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro-2.0](https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro-2.0) and preserves all the functionality of the original model.
+
 # Keynotes
 In comparison with [Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro](https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro),
 - Remove mode embedding, has smaller model size.
@@ -157,6 +159,15 @@ pipe.to("cuda")
 
 See `fp8_inference_example.py` for a complete example.
 
+# Pushing Model to Hugging Face Hub
+To push your FP8 quantized model to the Hugging Face Hub, use the included script:
+
+```bash
+python push_model_to_hub.py --repo_id "ABDALLALSWAITI/FLUX.1-dev-ControlNet-Union-Pro-2.0-fp8"
+```
+
+You will need to have the `huggingface_hub` library installed and be logged in with your Hugging Face credentials.
+
 # Resources
 - [InstantX/FLUX.1-dev-IP-Adapter](https://huggingface.co/InstantX/FLUX.1-dev-IP-Adapter)
 - [InstantX/FLUX.1-dev-Controlnet-Canny](https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Canny)