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ControlNet Streetview Safety Sd15 2

These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning. You can find some example images below.

ArtControlNetBasismodellrunwayml/stable-diffusion-v1-5VersionBBewertung

Modellquelle

Art
ControlNet
Dateigröße
1,35 GB
Basismodell
runwayml/stable-diffusion-v1-5
Version
vdiffusion_pytorch_model
Aktualisiert
7. Okt. 2026
Downloads
1
Quelle
Hugging Face

Quellenbeschreibung

controlnet-louistichelman/controlnet_streetview_safety_sd15_2

These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning. You can find some example images below.

prompt: A realistic and safe-looking street view in the USA. images_0) prompt: A realistic and dangerous-looking street view in the USA. images_1) prompt: A realistic and safe-looking street view in Brazil. images_2) prompt: A realistic and dangerous-looking street view in Brazil. images_3) prompt: A realistic and safe-looking street view in Romania. images_4) prompt: A realistic and dangerous-looking street view in Romania. images_5)

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]

Quellen

1 Quelle
Hugging FacePrimärVersion e840fe3c695a7548ee115ffa09556c457066b02a
huggingface.co/louistichelman/controlnet_streetview_safety_sd15_2/tree/e840fe3c695a7548ee115ffa09556c457066b02a

Verifiziert 7. Okt.

Modellartefakte

1 Artefakt

checkpoint-10000/controlnet/diffusion_pytorch_model.safetensors

safetensors · 1,35 GB · SHA-256 67b593b75471…cdf9 · Hugging Face

Download file

Quellenauszüge

3 Auszüge

--- license: creativeml-openrail-m library_name: diffusers tags: - stable-diffusion - stable-diffusion-diffusers - text-to-image - diffusers - controlnet - diffusers-training base_model: runwayml/stable-diffusion-v1-5 inference: true --- <!-- 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-louistichelman/controlnet_streetview_safety_sd15_2 These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning. You can find some example images below. prompt: A realistic and safe-looking street view in the USA. ![images_0)](./images_0.png) prompt: A realistic and dangerous-looking street view in the USA. ![images_1)](./images_1.png) prompt: A realistic and safe-looking street view in Brazil. ![images_2)](./images_2.png) prompt: A realistic and dangerous-looking street view in Brazil. ![images_3)](./images_3.png) prompt: A realistic and safe-looking street view in Romania. ![images_4)](./images_4.png) prompt: A realistic and dangerous-looking street view in Romania. ![images_5)](./images_5.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: 1 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo louistichelman/controlnet_streetview_safety_sd15_2

Source context: 10 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo louistichelman/controlnet_streetview_safety_sd15_2