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These are controlnet weights trained on SG161222/RealVisXLV4.0 with new type of conditioning.
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These are controlnet weights trained on SG161222/RealVisXL_V4.0 with new type of conditioning.
# TODO: add an example code snippet for running this diffusion pipeline
[TODO: provide examples of latent issues and potential remediations]
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1 QuelleVerifiziert 30. Juli
Modellartefakte
2 Artefaktecheckpoint-1000/controlnet/diffusion_pytorch_model.safetensors
safetensors · 4,66 GB · SHA-256 b9b141f4bb7c…c491 · Hugging Face
Herunterladendiffusion_pytorch_model.safetensors
safetensors · 4,66 GB · SHA-256 b9b141f4bb7c…c491 · Hugging Face
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2 Auszüge--- base_model: SG161222/RealVisXL_V4.0 library_name: diffusers license: openrail++ inference: true tags: - stable-diffusion-xl - stable-diffusion-xl-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-Vimax97/sdxl-controlnet-object-remover-test-03 These are controlnet weights trained on SG161222/RealVisXL_V4.0 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]
[TODO: describe the data used to train the model]
Source context: 2 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo Vimax97/sdxl-controlnet-object-remover-test-03