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SDXL ControlNet Deep Fash Test

These are controlnet weights trained on stabilityai/stable-diffusion-xl-base-1.0 with new type of conditioning.

Sourcehuggingface.co/Acopa/sdxl_controlnet_deep_fash_test/tree/3b99af399efc366fdecf24a482e419964716fecf
TypeControlNetModèle de basestabilityai/stable-diffusion-xl-base-1.0VersionBClasse

Source du modèle

Type
ControlNet
Taille du fichier
4,66 GB
Modèle de base
stabilityai/stable-diffusion-xl-base-1.0
Version
vdiffusion_pytorch_model
Mis à jour
8 oct. 2026
Téléchargements
2
Source
Hugging Face

Description de la source

controlnet-Acopa/sdxl_controlnet

These are controlnet weights trained on stabilityai/stable-diffusion-xl-base-1.0 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]

Sources

1 source
Hugging FacePrincipalVersion 3b99af399efc366fdecf24a482e419964716fecf
huggingface.co/Acopa/sdxl_controlnet_deep_fash_test/tree/3b99af399efc366fdecf24a482e419964716fecf

Vérifié 8 oct.

Artefacts du modèle

1 artefact

checkpoint-1000/controlnet/diffusion_pytorch_model.safetensors

safetensors · 4,66 GB · SHA-256 1c6a3575a06a…1bbc · Hugging Face

Download file

Extraits de sources

3 extraits
Readme31 juil.huggingface.co/Acopa/sdxl_controlnet_deep_fash_test

--- license: openrail++ library_name: diffusers tags: - stable-diffusion-xl - stable-diffusion-xl-diffusers - text-to-image - diffusers - controlnet - diffusers-training base_model: stabilityai/stable-diffusion-xl-base-1.0 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-Acopa/sdxl_controlnet These are controlnet weights trained on stabilityai/stable-diffusion-xl-base-1.0 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]

Note8 oct.huggingface.co/Acopa/sdxl_controlnet_deep_fash_test

Source context: 2 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo Acopa/sdxl_controlnet_deep_fash_test

Note31 juil.huggingface.co/Acopa/sdxl_controlnet_deep_fash_test

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