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--- |
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license: creativeml-openrail-m |
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language: |
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- en |
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tags: |
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- stable-diffusion |
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- diffusers |
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- text-to-image |
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--- |
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# SemiRealMix |
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The result of many merges aimed at making semi-realistic human images. |
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I use the following options to get good generation results: |
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#### Prompt: |
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delicate, masterpiece, best shadow, (1 girl:1.3), (korean girl:1.2), (from side:1.2), (from below:0.5), (photorealistic:1.5), extremely detailed skin, studio, beige background, warm soft light, low contrast, head tilt |
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#### Negative prompt: |
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(worst quality, low quality:1.4), nsfw, nude, (loli, child, infant, baby:1.5), jewely, (hard light:1.5), back light, spot light, hight contrast, (eyelid:1.3), outdoor, monochrome |
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Sampler: DPM++ SDE Karras |
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CFG Scale: 7 |
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Steps: 20 |
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Size: 512x768 |
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Denoising strength: 0.5, Hires upscale: 2, Hires upscaler: R-ESRGAN 4x+ Anime6B, Eta: 0.2 |
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Clip skip: 2 |
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Base Model : SD 1.5 |
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VAE: vae-ft-mse-840000-ema-pruned |
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Use xformers : True |
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## 🧨 Diffusers |
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This model can be used just like any other Stable Diffusion model. For more information, |
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please have a look at the [Stable Diffusion](https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion). |
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You can also export the model to [ONNX](https://huggingface.co/docs/diffusers/optimization/onnx), [MPS](https://huggingface.co/docs/diffusers/optimization/mps) and/or [FLAX/JAX](). |
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```python |
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from diffusers import StableDiffusionPipeline |
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import torch |
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model_id = "robotjung/SemiRealMix " |
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pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16) |
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pipe = pipe.to("cuda") |
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prompt = "1girl" |
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image = pipe(prompt).images[0] |
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image.save("./output.png") |
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``` |
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## Examples: |
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Here are some examples of images generated using this model: |
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