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These are controlnet weights trained on stabilityai/stable-diffusion-2-1-base with new type of conditioning. You can find some example images below.
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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: Woman in blue and black on a large plaza. images_0) prompt: A men's restroom showcasing the toilet through an open door. images_1) prompt: A man riding a kiteboard over the ocean under a cloudy sky. images_2) prompt: Two skiers stand on their skis in the snow. prompt: A meal of cheese toast, spaghetti, and broccoli on a white plate.
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1 fonteVerificado 31 de jul.
Artefatos de modelo
1 artefatocheckpoint-10360/controlnet/diffusion_pytorch_model.safetensors
safetensors · 1,36 GB · SHA-256 9c07ed1e7cdf…0b03 · Hugging Face
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2 trechos
# 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: 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 - 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-Amitz244/output_dir_controlnet 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: Woman in blue and black on a large plaza.  prompt: A men's restroom showcasing the toilet through an open door.  prompt: A man riding a kiteboard over the ocean under a cloudy sky.  prompt: Two skiers stand on their skis in the snow.  prompt: A meal of cheese toast, spaghetti, and broccoli on a white plate.  ## 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 Amitz244/output_dir_controlnet