Create README.md

README.md

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+---
+license: other
+language:
+- en
+base_model:
+- black-forest-labs/FLUX.1-dev
+pipeline_tag: text-to-image
+tags:
+- diffusers
+- controlnet
+- Flux
+- image-generation
+---
+
+# Description
+This repository provides a Diffusers version of FLUX.1-dev Depth ControlNet checkpoint by Xlabs AI, [original repo](https://huggingface.co/XLabs-AI/flux-controlnet-depth-v3). 
+
+![Example Picture 1](depth_result.png?raw=true)
+
+# How to use
+This model can be used directly with the diffusers library
+
+```
+import torch
+from diffusers.utils import load_image
+from diffusers import FluxControlNetModel
+from diffusers.pipelines import FluxControlNetPipeline
+from PIL import Image
+import numpy as np
+
+generator = torch.Generator(device="cuda").manual_seed(87544357)
+
+controlnet = FluxControlNetModel.from_pretrained(
+  "Xlabs-AI/flux-controlnet-depth-diffusers",
+  torch_dtype=torch.bfloat16,
+  use_safetensors=True,
+)
+pipe = FluxControlNetPipeline.from_pretrained(
+  "black-forest-labs/FLUX.1-dev",
+  controlnet=controlnet2,
+  torch_dtype=torch.bfloat16
+)
+pipe.to("cuda")
+
+control_image = load_image("https://huggingface.co/Xlabs-AI/flux-controlnet-depth-diffusers/resolve/main/depth_example.png")
+prompt = "photo of two people in the house, cinematic soft light"
+
+image = pipe(
+    prompt,
+    control_image=control_image,
+    controlnet_conditioning_scale=0.7,
+    num_inference_steps=25,
+    guidance_scale=3.5,
+    height=1024,
+    width=768,
+    generator=generator,
+    num_images_per_prompt=1,
+).images[0]
+
+image.save("output_test_controlnet.png")
+```
+
+## License
+
+Our weights fall under the [FLUX.1 [dev]](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md) Non-Commercial License<br/>