ControlNet
controlnet-80558303·3 events·first seen 28d agoAliases: ControlNet
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Train your ControlNet with diffusers
This Hugging Face blog post provides a technical guide for training ControlNet models using the diffusers library. It covers the process of conditioning diffusion models on additional inputs such as edge maps, depth maps, or other spatial signals to enable fine-grained image generation control. The post targets practitioners looking to implement custom ControlNet pipelines on their own datasets.
ControlNet in 🧨 Diffusers
Hugging Face's Diffusers library added support for ControlNet, a technique that enables fine-grained spatial and structural control over diffusion model image generation. The blog post covers how ControlNet conditions image synthesis on auxiliary inputs such as edge maps, depth maps, pose skeletons, and segmentation masks. This integration makes ControlNet-based generation accessible through the standard Diffusers pipeline API.
Efficient Controllable Generation for SDXL with T2I-Adapters
Hugging Face published a blog post detailing T2I-Adapters for Stable Diffusion XL (SDXL), a lightweight conditioning mechanism that enables controllable image generation without full fine-tuning. The approach allows users to guide SDXL outputs using structural signals such as depth maps, edge detection, and pose estimation. T2I-Adapters offer a parameter-efficient alternative to ControlNet for the SDXL architecture, with integration into the Diffusers library.