These are controlnet weights trained on benjamin-paine/stable-diffusion-v1-5 with new type of conditioning. You can find some example images below.
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These are controlnet weights trained on benjamin-paine/stable-diffusion-v1-5 with new type of conditioning. You can find some example images below.
prompt: a flower painting images_0) prompt: a flower painting, qrcode images_1)
Fuentes
1 fuenteVerificado 31 jul
Artefactos del modelo
1 artefactocheckpoint-10000/controlnet/diffusion_pytorch_model.safetensors
safetensors · 1,35 GB · SHA-256 ad89f24e37ca…1b3f · Hugging Face
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2 extractos# TODO: add an example code snippet for running this diffusion pipeline
[TODO: provide examples of latent issues and potential remediations]
[TODO: describe the data used to train the model]
--- base_model: benjamin-paine/stable-diffusion-v1-5 library_name: diffusers license: creativeml-openrail-m tags: - stable-diffusion - stable-diffusion-diffusers - text-to-image - diffusers - controlnet - diffusers-training 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-yuanqiuye/qrcode_controlnet_v2 These are controlnet weights trained on benjamin-paine/stable-diffusion-v1-5 with new type of conditioning. You can find some example images below. prompt: a flower painting  prompt: a flower painting, qrcode  ## 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: 0 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo yuanqiuye/qrcode_controlnet_v2