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Output Dir ControlNet

These are controlnet weights trained on stabilityai/stable-diffusion-2-1-base with new type of conditioning. You can find some example images below.

KindControlNetBase modelstabilityai/stable-diffusion-2-1-baseVersionBgrade

Model source

Kind
ControlNet
File size
1.36 GB
Base model
stabilityai/stable-diffusion-2-1-base
Version
vdiffusion_pytorch_model
Updated
Oct 8, 2026
Source
Hugging Face

Source description

controlnet-Amitz244/output_dir_controlnet

These are controlnet weights trained on stabilityai/stable-diffusion-2-1-base with new type of conditioning. You can find some example images below.

prompt: Woman in blue and black on a large plaza. images_0) prompt: A men's restroom showcasing the toilet through an open door. images_1) prompt: A man riding a kiteboard over the ocean under a cloudy sky. images_2) prompt: Two skiers stand on their skis in the snow. images_3) prompt: A meal of cheese toast, spaghetti, and broccoli on a white plate. images_4)

Intended uses & limitations

How to use

# TODO: add an example code snippet for running this diffusion pipeline

Limitations and bias

[TODO: provide examples of latent issues and potential remediations]

Training details

[TODO: describe the data used to train the model]

Sources

1 source
Hugging FacePrimaryVersion 50b350246ad27b291b46020fb79ad792775b0871
huggingface.co/Amitz244/output_dir_controlnet/tree/50b350246ad27b291b46020fb79ad792775b0871

Verified Oct 8

Model artifacts

1 artifact

checkpoint-10360/controlnet/diffusion_pytorch_model.safetensors

safetensors · 1.36 GB · SHA-256 9c07ed1e7cdf…0b03 · Hugging Face

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Source excerpts

2 excerpts

--- base_model: stabilityai/stable-diffusion-2-1-base library_name: diffusers license: creativeml-openrail-m inference: true tags: - stable-diffusion - stable-diffusion-diffusers - text-to-image - diffusers - controlnet - diffusers-training - stable-diffusion - stable-diffusion-diffusers - text-to-image - diffusers - controlnet - diffusers-training --- <!-- This model card has been generated automatically according to the information the training script had access to. You should probably proofread and complete it, then remove this comment. --> # controlnet-Amitz244/output_dir_controlnet These are controlnet weights trained on stabilityai/stable-diffusion-2-1-base with new type of conditioning. You can find some example images below. prompt: Woman in blue and black on a large plaza. ![images_0)](./images_0.png) prompt: A men's restroom showcasing the toilet through an open door. ![images_1)](./images_1.png) prompt: A man riding a kiteboard over the ocean under a cloudy sky. ![images_2)](./images_2.png) prompt: Two skiers stand on their skis in the snow. ![images_3)](./images_3.png) prompt: A meal of cheese toast, spaghetti, and broccoli on a white plate. ![images_4)](./images_4.png) ## Intended uses & limitations #### How to use ```python # TODO: add an example code snippet for running this diffusion pipeline ``` #### Limitations and bias [TODO: provide examples of latent issues and potential remediations] ## Training details [TODO: describe the data used to train the model]

Source context: 0 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo Amitz244/output_dir_controlnet