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@@ -66,20 +66,36 @@ Please follow the instructions in [mit-han-lab/nunchaku](https://github.com/mit-
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  ```python
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  import torch
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- from diffusers import FluxPipeline
 
 
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  from nunchaku.models.transformer_flux import NunchakuFluxTransformer2dModel
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- transformer = NunchakuFluxTransformer2dModel.from_pretrained("mit-han-lab/svdq-int4-flux.1-dev")
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- pipeline = FluxPipeline.from_pretrained(
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- "black-forest-labs/FLUX.1-dev", transformer=transformer, torch_dtype=torch.bfloat16
 
 
 
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  ).to("cuda")
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- image = pipeline("A cat holding a sign that says hello world", num_inference_steps=50, guidance_scale=3.5).images[0]
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- image.save("example.png")
 
 
 
 
 
 
 
 
 
 
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  ```
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  ### Comfy UI
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- roW
 
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  ## Limitations
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  ```python
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  import torch
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+ from diffusers import FluxControlPipeline
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+ from diffusers.utils import load_image
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+ from image_gen_aux import DepthPreprocessor
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  from nunchaku.models.transformer_flux import NunchakuFluxTransformer2dModel
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+ transformer = NunchakuFluxTransformer2dModel.from_pretrained("mit-han-lab/svdq-int4-flux.1-depth-dev")
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+
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+ pipe = FluxControlPipeline.from_pretrained(
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+ "black-forest-labs/FLUX.1-Depth-dev",
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+ transformer=transformer,
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+ torch_dtype=torch.bfloat16,
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  ).to("cuda")
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+
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+ prompt = "A robot made of exotic candies and chocolates of different kinds. The background is filled with confetti and celebratory gifts."
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+ control_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/robot.png")
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+
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+ processor = DepthPreprocessor.from_pretrained("LiheYoung/depth-anything-large-hf")
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+ control_image = processor(control_image)[0].convert("RGB")
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+
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+ image = pipe(
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+ prompt=prompt, control_image=control_image, height=1024, width=1024, num_inference_steps=30, guidance_scale=10.0
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+ ).images[0]
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+ image.save("flux.1-depth-dev.png")
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+
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  ```
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  ### Comfy UI
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+
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+ Work in progress. Stay tuned!
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  ## Limitations
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