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ControlNet Dot 20K 25000 v15

These are controlnet weights trained on stable-diffusion-v1-5/stable-diffusion-v1-5 with new type of conditioning.

ArtControlNetBasismodellstable-diffusion-v1-5/stable-diffusion-v1-5Versiondiffusion_pytorch_modelBBewertung

Modellquelle

Art
ControlNet
Dateigröße
1,35 GB
Basismodell
stable-diffusion-v1-5/stable-diffusion-v1-5
Version
vdiffusion_pytorch_model
Aktualisiert
7. Okt. 2026
Downloads
2
Quelle
Hugging Face

Quellenbeschreibung

controlnet-VivianYueh/Controlnet_dot_20K_25000_v15

These are controlnet weights trained on stable-diffusion-v1-5/stable-diffusion-v1-5 with new type of conditioning.

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 94b5393c9092aba19b1c7ab0e748780c61ff697f
huggingface.co/VivianYueh/Controlnet_dot_20K_25000_v15/tree/94b5393c9092aba19b1c7ab0e748780c61ff697f

Verifiziert 7. Okt.

Modellartefakte

1 Artefakt

diffusion_pytorch_model.safetensors

safetensors · 1,35 GB · SHA-256 b53bb13ac6b5…09c7 · Hugging Face

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Quellenauszüge

3 Auszüge

--- base_model: stable-diffusion-v1-5/stable-diffusion-v1-5 library_name: diffusers license: creativeml-openrail-m tags: - stable-diffusion - stable-diffusion-diffusers - text-to-image - diffusers - controlnet - diffusers-training 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-VivianYueh/Controlnet_dot_20K_25000_v15 These are controlnet weights trained on stable-diffusion-v1-5/stable-diffusion-v1-5 with new type of conditioning. ## 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: 2 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo VivianYueh/Controlnet_dot_20K_25000_v15

Source context: 3 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo VivianYueh/Controlnet_dot_20K_25000_v15