Upload README.md with huggingface_hub

README.md

@@ -146,7 +146,7 @@ from diffusers.utils import load_image
 from diffusers import FluxControlNetPipeline, FluxControlNetModel
 
 base_model = 'black-forest-labs/FLUX.1-dev'
-controlnet_model_union_fp8 = 'YOUR_USERNAME/FLUX.1-dev-ControlNet-Union-Pro-2.0-fp8'
+controlnet_model_union_fp8 = 'ABDALLALSWAITI/FLUX.1-dev-ControlNet-Union-Pro-2.0-fp8'
 
 # Load using FP8 data type
 controlnet = FluxControlNetModel.from_pretrained(controlnet_model_union_fp8, torch_dtype=torch.float8_e4m3fn)
@@ -162,7 +162,7 @@ See `fp8_inference_example.py` for a complete example.
 To push your FP8 quantized model to the Hugging Face Hub, use the included script:
 
 ```bash
-python push_model_to_hub.py --repo_id "YOUR_USERNAME/FLUX.1-dev-ControlNet-Union-Pro-2.0-fp8"
+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.