End of training
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- README.md +46 -0
- checkpoint-100/controlnet/config.json +22 -0
- checkpoint-100/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-100/optimizer.bin +3 -0
- checkpoint-100/random_states_0.pkl +3 -0
- checkpoint-100/scheduler.bin +3 -0
- checkpoint-1000/controlnet/config.json +22 -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-1100/controlnet/config.json +22 -0
- checkpoint-1100/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-1100/optimizer.bin +3 -0
- checkpoint-1100/random_states_0.pkl +3 -0
- checkpoint-1100/scheduler.bin +3 -0
- checkpoint-1200/controlnet/config.json +22 -0
- checkpoint-1200/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-1200/optimizer.bin +3 -0
- checkpoint-1200/random_states_0.pkl +3 -0
- checkpoint-1200/scheduler.bin +3 -0
- checkpoint-1300/controlnet/config.json +22 -0
- checkpoint-1300/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-1300/optimizer.bin +3 -0
- checkpoint-1300/random_states_0.pkl +3 -0
- checkpoint-1300/scheduler.bin +3 -0
- checkpoint-1400/controlnet/config.json +22 -0
- checkpoint-1400/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-1400/optimizer.bin +3 -0
- checkpoint-1400/random_states_0.pkl +3 -0
- checkpoint-1400/scheduler.bin +3 -0
- checkpoint-1500/controlnet/config.json +22 -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-1600/controlnet/config.json +22 -0
- checkpoint-1600/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-1600/optimizer.bin +3 -0
- checkpoint-1600/random_states_0.pkl +3 -0
- checkpoint-1600/scheduler.bin +3 -0
- checkpoint-1700/controlnet/config.json +22 -0
- checkpoint-1700/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-1700/optimizer.bin +3 -0
- checkpoint-1700/random_states_0.pkl +3 -0
- checkpoint-1700/scheduler.bin +3 -0
- checkpoint-1800/controlnet/config.json +22 -0
- checkpoint-1800/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-1800/optimizer.bin +3 -0
- checkpoint-1800/random_states_0.pkl +3 -0
README.md
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---
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base_model: stabilityai/stable-diffusion-3-medium-diffusers
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library_name: diffusers
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license: openrail++
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inference: true
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tags:
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- text-to-image
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- diffusers-training
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- diffusers
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- sd3
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- sd3-diffusers
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- controlnet
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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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# SD3 controlnet-forouzanfallah/sentinel_test5_percentile_caption2_bicubic_lpips_psnr
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These are controlnet weights trained on stabilityai/stable-diffusion-3-medium-diffusers with new type of conditioning.
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The weights were trained using [ControlNet](https://github.com/lllyasviel/ControlNet) with the [SD3 diffusers trainer](https://github.com/huggingface/diffusers/blob/main/examples/controlnet/README_sd3.md).
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You can find some example images below.
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prompt: a high-resolution satellite image, sharp details, clear view from space
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Please adhere to the licensing terms as described `[here](https://huggingface.co/stabilityai/stable-diffusion-3-medium/blob/main/LICENSE)`.
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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-100/controlnet/config.json
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{
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"_class_name": "SD3ControlNetModel",
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"_diffusers_version": "0.35.0.dev0",
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"_name_or_path": "stabilityai/stable-diffusion-3-medium-diffusers",
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"attention_head_dim": 64,
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"caption_projection_dim": 1536,
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"dual_attention_layers": [],
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"extra_conditioning_channels": 0,
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"force_zeros_for_pooled_projection": true,
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"in_channels": 16,
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"joint_attention_dim": 4096,
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"num_attention_heads": 24,
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"num_layers": 12,
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"out_channels": 16,
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"patch_size": 2,
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"pooled_projection_dim": 2048,
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"pos_embed_max_size": 192,
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"pos_embed_type": "sincos",
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"qk_norm": null,
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"sample_size": 128,
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"use_pos_embed": true
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}
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checkpoint-100/controlnet/diffusion_pytorch_model.safetensors
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checkpoint-1000/controlnet/config.json
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"_diffusers_version": "0.35.0.dev0",
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"_name_or_path": "stabilityai/stable-diffusion-3-medium-diffusers",
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"attention_head_dim": 64,
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"caption_projection_dim": 1536,
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"dual_attention_layers": [],
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"extra_conditioning_channels": 0,
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"out_channels": 16,
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"pos_embed_max_size": 192,
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"sample_size": 128,
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"use_pos_embed": true
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}
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}
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