zachary-shah commited on
Commit
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1 Parent(s): 0625dee

End of training

Browse files
README.md ADDED
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+
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+ ---
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+ license: creativeml-openrail-m
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+ base_model: yurman/mri-sd-v21-oasis
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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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+ inference: true
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+ ---
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+
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+ # controlnet-zachary-shah/controlnet-512-v21-full
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+
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+ These are controlnet weights trained on yurman/mri-sd-v21-oasis with new type of conditioning.
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+ You can find some example images below.
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+ prompt: An empty, flat black image with a MRI brain axial scan in the center
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+ ![images_0)](./images_0.png)
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+ prompt: An empty, flat black image with a MRI brain axial scan in the center
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+ ![images_1)](./images_1.png)
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+ prompt: An empty, flat black image with a MRI brain axial scan in the center
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+ ![images_2)](./images_2.png)
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+ prompt: An empty, flat black image with a MRI brain axial scan in the center
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+ ![images_3)](./images_3.png)
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+
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+ {
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+ "_diffusers_version": "0.26.0.dev0",
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+ "act_fn": "silu",
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+ "class_embed_type": null,
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+ "conditioning_channels": 3,
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+ "conditioning_embedding_out_channels": [
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+ 16,
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+ 32,
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+ 256
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+ ],
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+ "controlnet_conditioning_channel_order": "rgb",
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+ "cross_attention_dim": 1024,
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+ "down_block_types": [
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+ "CrossAttnDownBlock2D",
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+ "CrossAttnDownBlock2D",
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+ "CrossAttnDownBlock2D",
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+ "DownBlock2D"
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+ "flip_sin_to_cos": true,
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+ "in_channels": 4,
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+ "layers_per_block": 2,
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+ "mid_block_scale_factor": 1,
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+ "mid_block_type": "UNetMidBlock2DCrossAttn",
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+ "norm_eps": 1e-05,
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+ "transformer_layers_per_block": 1,
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+ "upcast_attention": true,
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+ "use_linear_projection": true
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