End of training
Browse files- .gitattributes +3 -0
- .gitignore +2 -0
- README.md +22 -0
- checkpoint-10000/optimizer.bin +3 -0
- checkpoint-10000/pytorch_model.bin +3 -0
- checkpoint-10000/random_states_0.pkl +3 -0
- checkpoint-10000/scaler.pt +3 -0
- checkpoint-10000/scheduler.bin +3 -0
- checkpoint-15000/optimizer.bin +3 -0
- checkpoint-15000/pytorch_model.bin +3 -0
- checkpoint-15000/random_states_0.pkl +3 -0
- checkpoint-15000/scaler.pt +3 -0
- checkpoint-15000/scheduler.bin +3 -0
- checkpoint-20000/optimizer.bin +3 -0
- checkpoint-20000/pytorch_model.bin +3 -0
- checkpoint-20000/random_states_0.pkl +3 -0
- checkpoint-20000/scaler.pt +3 -0
- checkpoint-20000/scheduler.bin +3 -0
- checkpoint-25000/optimizer.bin +3 -0
- checkpoint-25000/pytorch_model.bin +3 -0
- checkpoint-25000/random_states_0.pkl +3 -0
- checkpoint-25000/scaler.pt +3 -0
- checkpoint-25000/scheduler.bin +3 -0
- checkpoint-30000/optimizer.bin +3 -0
- checkpoint-30000/pytorch_model.bin +3 -0
- checkpoint-30000/random_states_0.pkl +3 -0
- checkpoint-30000/scaler.pt +3 -0
- checkpoint-30000/scheduler.bin +3 -0
- checkpoint-5000/optimizer.bin +3 -0
- checkpoint-5000/pytorch_model.bin +3 -0
- checkpoint-5000/random_states_0.pkl +3 -0
- checkpoint-5000/scaler.pt +3 -0
- checkpoint-5000/scheduler.bin +3 -0
- config.json +105 -0
- diffusion_pytorch_model.bin +3 -0
- diffusion_pytorch_model.safetensors +3 -0
- image_0.png +3 -0
- image_1.png +3 -0
- image_2.png +3 -0
.gitattributes
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@@ -32,3 +32,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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.gitignore
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step_*
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epoch_*
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README.md
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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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- lora
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- controlnet
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- control-lora
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inference: true
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---
|
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+
# ControlLoRA text2image fine-tuning - https://huggingface.co/wtcherr/sd-2m_random_5k_blur_61KS-model-control-lora
|
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+
These are ControlLoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were fine-tuned on the wtcherr/diffusiondb_2m_random_5k_blur_61KS dataset. You can find some example images in the following.
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![img_0](./image_0.png)
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![img_1](./image_1.png)
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![img_2](./image_2.png)
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{
|
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"_class_name": "ControlLoRA",
|
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"_diffusers_version": "0.17.0.dev0",
|
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"act_fn": "silu",
|
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"block_out_channels": [
|
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32,
|
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64,
|
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|
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256
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],
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"down_block_types": [
|
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"SimpleDownEncoderBlock2D",
|
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"SimpleDownEncoderBlock2D",
|
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"SimpleDownEncoderBlock2D",
|
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"SimpleDownEncoderBlock2D"
|
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],
|
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"in_channels": 3,
|
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"layers_per_block": 1,
|
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"lora_block_in_channels": [
|
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256,
|
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256,
|
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256
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],
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"lora_block_out_channels": [
|
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|
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|
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1280,
|
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1280
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],
|
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"lora_concat_hidden": false,
|
32 |
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"lora_control_channels": [
|
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null,
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null
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],
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"lora_control_rank": null,
|
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"lora_control_self_add": true,
|
40 |
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"lora_control_version": 1,
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"lora_cross_attention_dims": [
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[
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Git LFS Details
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Git LFS Details
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Git LFS Details
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