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Thermal Rgb ControlNet

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

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
5
Quelle
Hugging Face

Quellenbeschreibung

controlnet-swetha3456/thermal-rgb-controlnet

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

prompt: images_0) prompt: images_1) prompt: 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 bfcbcbf1372564518876fc5dfb9e8287dbea4070
huggingface.co/swetha3456/thermal-rgb-controlnet/tree/bfcbcbf1372564518876fc5dfb9e8287dbea4070

Verifiziert 7. Okt.

Modellartefakte

1 Artefakt

diffusion_pytorch_model.safetensors

safetensors · 1,35 GB · SHA-256 1f3927221580…9a81 · Hugging Face

Download file

Quellenauszüge

3 Auszüge

--- base_model: stable-diffusion-v1-5/stable-diffusion-v1-5 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-swetha3456/thermal-rgb-controlnet These are controlnet weights trained on stable-diffusion-v1-5/stable-diffusion-v1-5 with new type of conditioning. You can find some example images below. prompt: ![images_0)](./images_0.png) prompt: ![images_1)](./images_1.png) prompt: ![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: 5 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo swetha3456/thermal-rgb-controlnet

Source context: 6 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo swetha3456/thermal-rgb-controlnet