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Pcb ControlNet Sd2 1024

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

TypeControlNetModèle de basestabilityai/stable-diffusion-2-1-baseVersionBClasse

Source du modèle

Type
ControlNet
Taille du fichier
1,36 GB
Modèle de base
stabilityai/stable-diffusion-2-1-base
Version
vdiffusion_pytorch_model
Mis à jour
7 oct. 2026
Téléchargements
5
Source
Hugging Face

Description de la source

controlnet-pribadihcr/pcb_controlnet_sd2_1024

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: a photo of sks pcb contain 8 defects. images_0)

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 ca87d7efb39522b11645776b01a48e8ba75903e1
huggingface.co/pribadihcr/pcb_controlnet_sd2_1024/tree/ca87d7efb39522b11645776b01a48e8ba75903e1

Vérifié 7 oct.

Artefacts du modèle

1 artefact

checkpoint-1000/controlnet/diffusion_pytorch_model.safetensors

safetensors · 1,36 GB · SHA-256 35999487e721…5ce6 · Hugging Face

Download file

Extraits de sources

3 extraits

--- 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 --- <!-- 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-pribadihcr/pcb_controlnet_sd2_1024 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: a photo of sks pcb contain 8 defects. ![images_0)](./images_0.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: 5 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo pribadihcr/pcb_controlnet_sd2_1024

Source context: 4 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo pribadihcr/pcb_controlnet_sd2_1024