louistichelman
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- README.md +55 -0
- checkpoint-10000/controlnet/config.json +51 -0
- checkpoint-10000/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-10000/optimizer.bin +3 -0
- checkpoint-10000/random_states_0.pkl +3 -0
- checkpoint-10000/scheduler.bin +3 -0
- checkpoint-15000/controlnet/config.json +51 -0
- checkpoint-15000/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-15000/optimizer.bin +3 -0
- checkpoint-15000/random_states_0.pkl +3 -0
- checkpoint-15000/scheduler.bin +3 -0
- checkpoint-20000/controlnet/config.json +51 -0
- checkpoint-20000/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-20000/optimizer.bin +3 -0
- checkpoint-20000/random_states_0.pkl +3 -0
- checkpoint-20000/scheduler.bin +3 -0
- checkpoint-25000/controlnet/config.json +51 -0
- checkpoint-25000/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-25000/optimizer.bin +3 -0
- checkpoint-25000/random_states_0.pkl +3 -0
- checkpoint-25000/scheduler.bin +3 -0
- checkpoint-30000/controlnet/config.json +51 -0
- checkpoint-30000/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-30000/optimizer.bin +3 -0
- checkpoint-30000/random_states_0.pkl +3 -0
- checkpoint-30000/scheduler.bin +3 -0
- checkpoint-35000/controlnet/config.json +51 -0
- checkpoint-35000/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-35000/optimizer.bin +3 -0
- checkpoint-35000/random_states_0.pkl +3 -0
- checkpoint-35000/scheduler.bin +3 -0
- checkpoint-40000/controlnet/config.json +51 -0
- checkpoint-40000/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-40000/optimizer.bin +3 -0
- checkpoint-40000/random_states_0.pkl +3 -0
- checkpoint-40000/scheduler.bin +3 -0
- checkpoint-45000/controlnet/config.json +51 -0
- checkpoint-45000/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-45000/optimizer.bin +3 -0
- checkpoint-45000/random_states_0.pkl +3 -0
- checkpoint-45000/scheduler.bin +3 -0
- checkpoint-5000/controlnet/config.json +51 -0
- checkpoint-5000/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-5000/optimizer.bin +3 -0
- checkpoint-5000/random_states_0.pkl +3 -0
- checkpoint-5000/scheduler.bin +3 -0
- checkpoint-50000/controlnet/config.json +51 -0
- checkpoint-50000/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-50000/optimizer.bin +3 -0
- checkpoint-50000/random_states_0.pkl +3 -0
README.md
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---
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license: creativeml-openrail-m
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library_name: diffusers
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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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base_model: runwayml/stable-diffusion-v1-5
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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-louistichelman/controlnet_streetview_segmentation_res400
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These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning.
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You can find some example images below.
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prompt: A realistic google streetview image, which was assigned a beauty-score of 16.616573, where scores are between 10 and 40 and higher scores indicate more beauty.
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![images_0)](./images_0.png)
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prompt: A realistic google streetview image, which was assigned a beauty-score of 35.616573, where scores are between 10 and 40 and higher scores indicate more beauty.
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![images_1)](./images_1.png)
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prompt: A realistic google streetview image, which was assigned a beauty-score of 16.616573, where scores are between 10 and 40 and higher scores indicate more beauty.
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![images_2)](./images_2.png)
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prompt: A realistic google streetview image, which was assigned a beauty-score of 35.616573, where scores are between 10 and 40 and higher scores indicate more beauty.
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![images_3)](./images_3.png)
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prompt: A realistic google streetview image, which was assigned a beauty-score of 30.058624, where scores are between 10 and 40 and higher scores indicate more beauty.
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![images_4)](./images_4.png)
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prompt: A realistic google streetview image, which was assigned a beauty-score of 35.512676, where scores are between 10 and 40 and higher scores indicate more beauty.
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![images_5)](./images_5.png)
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prompt: A realistic google streetview image, which was assigned a beauty-score of 33.00086, where scores are between 10 and 40 and higher scores indicate more beauty.
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![images_6)](./images_6.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]
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checkpoint-10000/controlnet/config.json
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{
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"_class_name": "ControlNetModel",
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"_diffusers_version": "0.29.0.dev0",
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"act_fn": "silu",
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"addition_embed_type": null,
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"addition_embed_type_num_heads": 64,
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"addition_time_embed_dim": null,
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"attention_head_dim": 8,
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"block_out_channels": [
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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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],
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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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"downsample_padding": 1,
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"encoder_hid_dim": null,
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"flip_sin_to_cos": true,
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"freq_shift": 0,
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"global_pool_conditions": false,
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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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"norm_num_groups": 32,
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"resnet_time_scale_shift": "default",
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"transformer_layers_per_block": 1,
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"upcast_attention": false,
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"use_linear_projection": false
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}
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checkpoint-10000/controlnet/diffusion_pytorch_model.safetensors
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checkpoint-15000/controlnet/config.json
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"mid_block_scale_factor": 1,
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checkpoint-20000/controlnet/diffusion_pytorch_model.safetensors
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