End of training
Browse filesThis view is limited to 50 files because it contains too many changes.
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- README.md +45 -0
- checkpoint-1000/controlnet/config.json +56 -0
- checkpoint-1000/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-1000/optimizer.bin +3 -0
- checkpoint-1000/random_states_0.pkl +3 -0
- checkpoint-1000/scheduler.bin +3 -0
- checkpoint-1500/controlnet/config.json +56 -0
- checkpoint-1500/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-1500/optimizer.bin +3 -0
- checkpoint-1500/random_states_0.pkl +3 -0
- checkpoint-1500/scheduler.bin +3 -0
- checkpoint-2000/controlnet/config.json +56 -0
- checkpoint-2000/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-2000/optimizer.bin +3 -0
- checkpoint-2000/random_states_0.pkl +3 -0
- checkpoint-2000/scheduler.bin +3 -0
- checkpoint-2500/controlnet/config.json +56 -0
- checkpoint-2500/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-2500/optimizer.bin +3 -0
- checkpoint-2500/random_states_0.pkl +3 -0
- checkpoint-2500/scheduler.bin +3 -0
- checkpoint-3000/controlnet/config.json +56 -0
- checkpoint-3000/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-3000/optimizer.bin +3 -0
- checkpoint-3000/random_states_0.pkl +3 -0
- checkpoint-3000/scheduler.bin +3 -0
- checkpoint-3500/controlnet/config.json +56 -0
- checkpoint-3500/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-3500/optimizer.bin +3 -0
- checkpoint-3500/random_states_0.pkl +3 -0
- checkpoint-3500/scheduler.bin +3 -0
- checkpoint-4000/controlnet/config.json +56 -0
- checkpoint-4000/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-4000/optimizer.bin +3 -0
- checkpoint-4000/random_states_0.pkl +3 -0
- checkpoint-4000/scheduler.bin +3 -0
- checkpoint-4500/controlnet/config.json +56 -0
- checkpoint-4500/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-4500/optimizer.bin +3 -0
- checkpoint-4500/random_states_0.pkl +3 -0
- checkpoint-4500/scheduler.bin +3 -0
- checkpoint-500/controlnet/config.json +56 -0
- checkpoint-500/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-500/optimizer.bin +3 -0
- checkpoint-500/random_states_0.pkl +3 -0
- checkpoint-500/scheduler.bin +3 -0
- checkpoint-5000/controlnet/config.json +56 -0
- checkpoint-5000/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-5000/optimizer.bin +3 -0
- checkpoint-5000/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: stabilityai/stable-diffusion-2-1-base
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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-Wouter01/really_good_diffusion_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:
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![images_0)](./images_0.png)
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prompt:
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![images_1)](./images_1.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-1000/controlnet/config.json
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{
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"_class_name": "ControlNetModel",
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"_diffusers_version": "0.28.0.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": [
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"block_out_channels": [
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"conditioning_channels": 3,
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"conditioning_embedding_out_channels": [
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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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],
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"downsample_padding": 1,
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"encoder_hid_dim": null,
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"encoder_hid_dim_type": 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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"num_attention_heads": null,
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"only_cross_attention": false,
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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": true
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}
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checkpoint-1500/controlnet/config.json
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"use_linear_projection": true
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}
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checkpoint-1500/controlnet/diffusion_pytorch_model.safetensors
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}
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checkpoint-2000/controlnet/diffusion_pytorch_model.safetensors
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