Zum Inhalt springen
ModelAufgelistetExtern
Herunterladen

Old ControlNet 1

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
8. Okt. 2026
Downloads
2
Quelle
Hugging Face

Quellenbeschreibung

controlnet-tempertrash/model_out

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 photography of a woman with a smile on her face images_0) prompt: a close up of a passion flower images_1) prompt: a couple laying on the beach images_2)

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 4086a1bfc582a10d1eeedbb642c147bb9af9601b
huggingface.co/tempertrash/old_controlnet_1/tree/4086a1bfc582a10d1eeedbb642c147bb9af9601b

Verifiziert 8. Okt.

Modellartefakte

1 Artefakt

checkpoint-10/controlnet/diffusion_pytorch_model.safetensors

safetensors · 1,35 GB · SHA-256 e8dafc47ee62…b442 · 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-tempertrash/model_out 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 photography of a woman with a smile on her face ![images_0)](./images_0.png) prompt: a close up of a passion flower ![images_1)](./images_1.png) prompt: a couple laying on the beach ![images_2)](./images_2.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: 2 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo tempertrash/old_controlnet_1

Source context: 0 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo tempertrash/old_controlnet_1