stabilityai/stable-diffusion-3.5-large-controlnet-depth

text-to-image model by stabilityai

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Model card & documentation

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This repository provides the Depth ControlNet for Stable Diffusion 3.5 Large.. Please note: This model is released under the Stability Community License. Visit Stability AI to learn or contact us for commercial licensing details. Here are the key components of the license: For organizations with annual revenue more than $1M, please contact us here to inquire about an Enterprise License. Install the repo: Then, download the models and sample image like so: and then you can run Which should give you an image like below: Make sure you upgrade to the latest diffusers version: pip install -U diffusers. And then you can run: You can use imagegenaux to extract depthimage, which contains all the preprocessor required to use with diffusers pipelines. An input image can be preprocessed for control use following the code snippet below. SD3.5 does not implement this behavior, so we recommend doing so in an external script…

stabilityai/stable-diffusion-3.5-large-controlnet-depth on Hugging Face A short preview, not the full document.

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Model overview

stabilityai/stable-diffusion-3.5-large-controlnet-depth is a text-to-image model repository published by stabilityai on Hugging Face. The source reports the diffusers library.

This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.

Model facts

Task: text-to-image
Library: diffusers
Recent downloads (30 days): 51,115
Cumulative likes: 15
Hugging Face trending score: 0
Reported safetensors parameters: 2,153,518,976
Architecture: Not reported
License: other
Access: Not gated by Hugging Face
Created: 2024-11-25T18:34:37.000Z
Last modified: 2024-11-28T00:56:12.000Z

Compatibility and lineage

Reported languages: en

Base-model lineage was not included.

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

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Model card and usage instructions

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