End of training
Browse files- .gitattributes +2 -0
- README.md +43 -0
- checkpoint-200/controlnet/config.json +56 -0
- checkpoint-200/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-200/optimizer.bin +3 -0
- checkpoint-200/random_states_0.pkl +3 -0
- checkpoint-200/scheduler.bin +3 -0
- checkpoint-400/controlnet/config.json +56 -0
- checkpoint-400/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-400/optimizer.bin +3 -0
- checkpoint-400/random_states_0.pkl +3 -0
- checkpoint-400/scheduler.bin +3 -0
- checkpoint-600/controlnet/config.json +56 -0
- checkpoint-600/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-600/optimizer.bin +3 -0
- checkpoint-600/random_states_0.pkl +3 -0
- checkpoint-600/scheduler.bin +3 -0
- checkpoint-800/controlnet/config.json +56 -0
- checkpoint-800/controlnet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-800/optimizer.bin +3 -0
- checkpoint-800/random_states_0.pkl +3 -0
- checkpoint-800/scheduler.bin +3 -0
- config.json +56 -0
- diffusion_pytorch_model.safetensors +3 -0
- image_control.png +3 -0
- images_0.png +3 -0
.gitattributes
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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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image_control.png filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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2 |
+
base_model: stabilityai/stable-diffusion-2-1-base
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+
library_name: diffusers
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+
license: creativeml-openrail-m
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inference: true
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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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+
---
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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-ethantqiu/big_lr_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: A plate of tomatoes and avocado.
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+
![images_0)](./images_0.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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+
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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-200/controlnet/config.json
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{
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"_class_name": "ControlNetModel",
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|
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"act_fn": "silu",
|
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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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"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
|
56 |
+
}
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checkpoint-200/controlnet/diffusion_pytorch_model.safetensors
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checkpoint-400/controlnet/config.json
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"down_block_types": [
|
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|
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|
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"use_linear_projection": true
|
56 |
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}
|
checkpoint-400/controlnet/diffusion_pytorch_model.safetensors
ADDED
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checkpoint-600/controlnet/config.json
ADDED
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"cross_attention_dim": 1024,
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"down_block_types": [
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|
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"CrossAttnDownBlock2D",
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|
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"use_linear_projection": true
|
56 |
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}
|
checkpoint-600/controlnet/diffusion_pytorch_model.safetensors
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