Update README.md

README.md

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----
-license: other
-license_name: bria-legal-lobby
-license_link: https://bria.ai/legal-lobby
----
+---
+license: other
+license_name: bria-legal-lobby
+license_link: https://bria.ai/legal-lobby
+---
+
+
+# BRIA 3.0 ControlNet Union Model Card
+
+
+BRIA-3.0 ControlNet-Union, trained on the foundation of [BRIA-3.0 Text-to-Image](https://huggingface.co/briaai/BRIA-3.0-TOUCAN)
+
+[CLICK HERE FOR A DEMO](https://huggingface.co/spaces/briaai/BRIA-2.3-ControlNet-Pose)
+
+[BRIA 3.0](https://huggingface.co/briaai/BRIA-3.0-TOUCAN) was trained from scratch exclusively on licensed data from our esteemed data partners. Therefore, they are safe for commercial use and provide full legal liability coverage for copyright and privacy infringement, as well as harmful content mitigation. That is, our dataset does not contain copyrighted materials, such as fictional characters, logos, trademarks, public figures, harmful content, or privacy-infringing content.
+
+Join our [Discord community](https://discord.gg/Nxe9YW9zHS) for more information, tutorials, tools, and to connect with other users!
+
+![controlnet_pose_showoff.png](https://huggingface.co/briaai/BRIA-2.3-ControlNet-Pose/resolve/main/controlnet_pose_showoff.png)
+
+
+### Model Description
+- **Developed by:** BRIA AI
+- **Model type:** [ControlNet](https://huggingface.co/docs/diffusers/using-diffusers/controlnet) for Latent diffusion
+- **License:** [bria-3.0](https://bria.ai/bria-huggingface-model-license-agreement/)
+
+- **Model Description:** ControlNet Union for BRIA 3.0  Text-to-Image model. The model generates images guided by text and a conditioned image.
+- **Resources for more information:** [BRIA AI](https://bria.ai/)
+
+
+### Get Access
+BRIA 3.0 ControlNet-Union requires access to BRIA 3.0 Text-to-Image. For more information, [click here](https://huggingface.co/briaai/BRIA-3.0-TOUCAN).
+
+
+## Control Mode
+
+| Control Mode | Description |
+|:------------:|:-----------:|
+|0|depth
+|1|canny
+|2|colorgrid
+|3|recolor
+|4|tlie
+|5|pose
+
+
+# Inference
+```python
+pip install diffusers==0.30.2, hf_hub_download
+```
+
+```python
+from huggingface_hub import hf_hub_download
+import os
+
+try:
+    local_dir = os.path.dirname(__file__)
+except:
+    local_dir = '.'
+    
+hf_hub_download(repo_id="briaai/BRIA-3.0-TOUCAN", filename='pipeline_bria.py', local_dir=local_dir)
+hf_hub_download(repo_id="briaai/BRIA-3.0-TOUCAN", filename='transformer_bria.py', local_dir=local_dir)
+hf_hub_download(repo_id="briaai/BRIA-3.0-TOUCAN", filename='bria_utils.py', local_dir=local_dir)
+hf_hub_download(repo_id="briaai/BRIA-3.0-ControlNet-Union", filename='pipeline_bria_controlnet.py', local_dir=local_dir)
+hf_hub_download(repo_id="briaai/BRIA-3.0-ControlNet-Union", filename='controlnet_bria.py', local_dir=local_dir)
+
+
+import torch
+from diffusers.utils import load_image
+from controlnet_bria import BriaControlNetModel, BriaMultiControlNetModel
+from pipeline_bria_controlnet import BriaControlNetPipeline
+
+<!-- from diffusers import FluxControlNetPipeline, FluxControlNetModel -->
+
+base_model = 'briaai/BRIA-3.0-TOUCAN'
+controlnet_model = 'briaai/BRIA-3.0-ControlNet-Union'
+
+controlnet = BriaControlNetModel.from_pretrained(controlnet_model, torch_dtype=torch.bfloat16)
+pipe = BriaControlNetPipeline.from_pretrained(base_model, controlnet=controlnet, torch_dtype=torch.bfloat16)
+pipe.to("cuda")
+
+control_image_canny = load_image("https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union-alpha/resolve/main/images/canny.jpg")
+controlnet_conditioning_scale = 0.5
+control_mode = 0
+
+width, height = control_image.size
+
+prompt = 'A bohemian-style female travel blogger with sun-kissed skin and messy beach waves.'
+
+image = pipe(
+    prompt, 
+    control_image=control_image,
+    control_mode=control_mode,
+    width=width,
+    height=height,
+    controlnet_conditioning_scale=controlnet_conditioning_scale,
+    num_inference_steps=24, 
+    guidance_scale=3.5,
+).images[0]
+image.save("image.jpg")
+```
+
+# Multi-Controls Inference
+```python
+import torch
+from diffusers.utils import load_image
+from diffusers import FluxControlNetPipeline, FluxControlNetModel, FluxMultiControlNetModel
+
+base_model = 'black-forest-labs/FLUX.1-dev'
+controlnet_model_union = 'InstantX/FLUX.1-dev-Controlnet-Union'
+
+controlnet_union = FluxControlNetModel.from_pretrained(controlnet_model_union, torch_dtype=torch.bfloat16)
+controlnet = FluxMultiControlNetModel([controlnet_union]) # we always recommend loading via FluxMultiControlNetModel
+
+pipe = FluxControlNetPipeline.from_pretrained(base_model, controlnet=controlnet, torch_dtype=torch.bfloat16)
+pipe.to("cuda")
+
+prompt = 'A bohemian-style female travel blogger with sun-kissed skin and messy beach waves.'
+control_image_depth = load_image("https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union/resolve/main/images/depth.jpg")
+control_mode_depth = 2
+
+control_image_canny = load_image("https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union/resolve/main/images/canny.jpg")
+control_mode_canny = 0
+
+width, height = control_image.size
+
+image = pipe(
+    prompt, 
+    control_image=[control_image_depth, control_image_canny],
+    control_mode=[control_mode_depth, control_mode_canny],
+    width=width,
+    height=height,
+    controlnet_conditioning_scale=[0.2, 0.4],
+    num_inference_steps=24, 
+    guidance_scale=3.5,
+    generator=torch.manual_seed(42),
+).images[0]
+
+```
+
+# Resources
+- [InstantX/FLUX.1-dev-Controlnet-Canny](https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Canny)
+- [InstantX/FLUX.1-dev-Controlnet-Union](https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union)
+- [Shakker-Labs/FLUX.1-dev-ControlNet-Depth](https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Depth)
+- [Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro](https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro)
+
+# Acknowledgements
+Thanks [zzzzzero](https://github.com/zzzzzero) for help us pointing out some bugs in the training.