YiYiXu commited on
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End of training

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.gitattributes CHANGED
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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: runwayml/stable-diffusion-v1-5
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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- jax-diffusers-event/canny-coyo1m
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+
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+ These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning. You can find some example images in the following.
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+
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+ prompt: car, a detailed high-quality professional image
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+ ![images_0)](./images_0.png)
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+ prompt: A house on the water with a small yacht out front, a detailed high-quality professional image
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+ ![images_1)](./images_1.png)
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+ prompt: man with polo shirt, a detailed high-quality professional image
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+ ![images_2)](./images_2.png)
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+ prompt: sneaker, a detailed high-quality professional image
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+ ![images_3)](./images_3.png)
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+
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+ {
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+ "_class_name": "FlaxControlNetModel",
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+ "_diffusers_version": "0.15.0.dev0",
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+ "attention_head_dim": 8,
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+ "block_out_channels": [
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+ 320,
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+ 640,
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+ 1280,
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+ 1280
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+ ],
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+ "conditioning_embedding_out_channels": [
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+ 16,
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+ 32,
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+ 96,
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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": 768,
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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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+ ],
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+ "dropout": 0.0,
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+ "flip_sin_to_cos": true,
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+ "freq_shift": 0,
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+ "in_channels": 4,
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+ "layers_per_block": 2,
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+ "only_cross_attention": false,
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+ "sample_size": 32,
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+ "use_linear_projection": false
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+ }
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