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--- |
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base_model: stabilityai/stable-diffusion-2-1-base |
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library_name: diffusers |
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license: creativeml-openrail-m |
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tags: |
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- stable-diffusion |
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- stable-diffusion-diffusers |
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- text-to-image |
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- diffusers |
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- controlnet |
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- diffusers-training |
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inference: true |
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--- |
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<!-- This model card has been generated automatically according to the information the training script had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# controlnet-Jieya/model_out |
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These are controlnet weights trained on stabilityai/stable-diffusion-2-1-base with new type of conditioning. |
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You can find some example images below. |
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prompt: High-quality close-up dslr photo of man wearing a hat with trees in the background |
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![images_0)](./images_0.png) |
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prompt: Girl smiling, professional dslr photograph, dark background, studio lights, high quality |
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![images_1)](./images_1.png) |
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prompt: Portrait of a clown face, oil on canvas, bittersweet expression |
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![images_2)](./images_2.png) |
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## Intended uses & limitations |
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#### How to use |
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```python |
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# TODO: add an example code snippet for running this diffusion pipeline |
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``` |
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#### Limitations and bias |
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[TODO: provide examples of latent issues and potential remediations] |
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## Training details |
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[TODO: describe the data used to train the model] |