Update README.md

README.md

@@ -17,9 +17,10 @@ base_model: black-forest-labs/FLUX.1-dev
 <img src="./images/image_demo_weight.png" width = "800" />
 
 
-Diffusers version: until the next Diffusers pypi release, 
-please install Diffusers from source and use [this PR](https://github.com/huggingface/diffusers/pull/9126) to be able to use FLUX controlnet. 
-TODO: change when new version.
+Diffusers version:
+```shell
+pip install -U diffusers
+```
 
 
 
@@ -32,12 +33,12 @@ from diffusers.pipelines.flux.pipeline_flux_controlnet import FluxControlNetPipe
 from diffusers.models.controlnet_flux import FluxControlNetModel
 
 base_model = 'black-forest-labs/FLUX.1-dev'
-controlnet_model = 'InstantX/FLUX.1-dev-Controlnet-Canny-alpha'
+controlnet_model = 'InstantX/FLUX.1-dev-Controlnet-Canny'
 controlnet = FluxControlNetModel.from_pretrained(controlnet_model, torch_dtype=torch.bfloat16)
 pipe = FluxControlNetPipeline.from_pretrained(base_model, controlnet=controlnet, torch_dtype=torch.bfloat16)
 pipe.to("cuda")
 
-control_image = load_image("https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Canny-alpha/resolve/main/canny.jpg")
+control_image = load_image("https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Canny/resolve/main/canny.jpg")
 prompt = "A girl in city, 25 years old, cool, futuristic"
 image = pipe(
     prompt, 
@@ -50,6 +51,8 @@ image.save("image.jpg")
 ```
 
 
-## Limitation
-The current weights are trained on 512x512, but inference can still be performed on non-512 sizes. 
-The latest 1024 + multi-scale model is under training, and it will be synchronized and open-sourced on HF afterwards.
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