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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.
Source du modèle
Description de la source
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)
# TODO: add an example code snippet for running this diffusion pipeline
Sources
1 sourceVérifié 30 juil.
Artefacts du modèle
1 artefactcheckpoint-1000/controlnet/diffusion_pytorch_model.safetensors
safetensors · 1,35 GB · SHA-256 bd77a71a4be9…5526 · Hugging Face
TéléchargerExtraits de sources
2 extraits[TODO: provide examples of latent issues and potential remediations]
[TODO: describe the data used to train the model]
--- 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-v2-no-prompts 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:  prompt:  ## 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: 4 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo swetha3456/thermal-rgb-controlnet-v2-no-prompts