End of training
Browse filesThis view is limited to 50 files because it contains too many changes.
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- .gitattributes +1 -0
- README.md +45 -0
- checkpoint-10000/controlnet/config.json +52 -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
- config.json +52 -0
- diffusion_pytorch_model.safetensors +3 -0
- image_control.png +0 -0
- images_0.png +3 -0
- images_1.png +0 -0
- logs/train_controlnet/1715366252.4852138/events.out.tfevents.1715366252.caed24b55d5a.7147.1 +3 -0
- logs/train_controlnet/1715366252.4893303/hparams.yml +50 -0
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- logs/train_controlnet/1715374661.5201998/hparams.yml +50 -0
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- logs/train_controlnet/1715374747.38308/hparams.yml +50 -0
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- logs/train_controlnet/1715374817.528899/hparams.yml +50 -0
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- logs/train_controlnet/1715375449.054004/hparams.yml +50 -0
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- logs/train_controlnet/1715378397.6396842/hparams.yml +50 -0
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- logs/train_controlnet/1715393609.436095/hparams.yml +50 -0
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- logs/train_controlnet/events.out.tfevents.1715393609.caed24b55d5a.8636.0 +3 -0
.gitattributes
CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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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-awang11/fill50k_diffusion_test
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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: red circle with blue background
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![images_0)](./images_0.png)
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prompt: cyan circle with brown floral background
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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-10000/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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"down_block_types": [
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"CrossAttnDownBlock2D",
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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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"use_linear_projection": false
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}
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checkpoint-10000/controlnet/diffusion_pytorch_model.safetensors
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config.json
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image_control.png
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images_0.png
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Git LFS Details
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images_1.png
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logs/train_controlnet/1715366252.4852138/events.out.tfevents.1715366252.caed24b55d5a.7147.1
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dataset_name: fusing/fill50k
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lr_num_cycles: 1
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lr_power: 1.0
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lr_scheduler: constant
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lr_warmup_steps: 500
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max_grad_norm: 1.0
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max_train_samples: null
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max_train_steps: 12500
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num_train_epochs: 1
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output_dir: /root/workspace/models
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pretrained_model_name_or_path: runwayml/stable-diffusion-v1-5
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