End of training
Browse files- README.md +39 -0
- checkpoint-1000/controlnet/config.json +57 -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/scaler.pt +3 -0
- checkpoint-1000/scheduler.bin +3 -0
- checkpoint-1500/controlnet/config.json +57 -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/scaler.pt +3 -0
- checkpoint-1500/scheduler.bin +3 -0
- checkpoint-2000/controlnet/config.json +57 -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/scaler.pt +3 -0
- checkpoint-2000/scheduler.bin +3 -0
- checkpoint-2500/controlnet/config.json +57 -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/scaler.pt +3 -0
- checkpoint-2500/scheduler.bin +3 -0
- checkpoint-500/controlnet/config.json +57 -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/scaler.pt +3 -0
- checkpoint-500/scheduler.bin +3 -0
- config.json +57 -0
- diffusion_pytorch_model.safetensors +3 -0
README.md
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---
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license: openrail++
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library_name: diffusers
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tags:
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- stable-diffusion-xl
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- stable-diffusion-xl-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-xl-base-1.0
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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-Acopa/sdxl_controlnet
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These are controlnet weights trained on stabilityai/stable-diffusion-xl-base-1.0 with new type of conditioning.
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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": "text_time",
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"addition_embed_type_num_heads": 64,
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"addition_time_embed_dim": 256,
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"attention_head_dim": [
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5,
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10,
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20
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],
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"block_out_channels": [
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320,
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640,
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1280
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],
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"class_embed_type": null,
|
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"conditioning_channels": 3,
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"conditioning_embedding_out_channels": [
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16,
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32,
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96,
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256
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],
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"controlnet_conditioning_channel_order": "rgb",
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"cross_attention_dim": 2048,
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"down_block_types": [
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"DownBlock2D",
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"CrossAttnDownBlock2D",
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"CrossAttnDownBlock2D"
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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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44 |
+
"norm_num_groups": 32,
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45 |
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"num_attention_heads": null,
|
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"num_class_embeds": null,
|
47 |
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"only_cross_attention": false,
|
48 |
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"projection_class_embeddings_input_dim": 2816,
|
49 |
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"resnet_time_scale_shift": "default",
|
50 |
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"transformer_layers_per_block": [
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51 |
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1,
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2,
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10
|
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],
|
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"upcast_attention": null,
|
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"use_linear_projection": true
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+
}
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checkpoint-1000/controlnet/diffusion_pytorch_model.safetensors
ADDED
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checkpoint-1000/optimizer.bin
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checkpoint-1000/scheduler.bin
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checkpoint-1500/controlnet/config.json
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{
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"_class_name": "ControlNetModel",
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3 |
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"_diffusers_version": "0.28.0.dev0",
|
4 |
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"act_fn": "silu",
|
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"addition_embed_type": "text_time",
|
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"addition_embed_type_num_heads": 64,
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"addition_time_embed_dim": 256,
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"attention_head_dim": [
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"block_out_channels": [
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],
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"class_embed_type": null,
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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": 2048,
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"down_block_types": [
|
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"DownBlock2D",
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"CrossAttnDownBlock2D",
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"CrossAttnDownBlock2D"
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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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"num_class_embeds": null,
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"only_cross_attention": false,
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"projection_class_embeddings_input_dim": 2816,
|
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"resnet_time_scale_shift": "default",
|
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"transformer_layers_per_block": [
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],
|
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"upcast_attention": null,
|
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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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checkpoint-1500/optimizer.bin
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checkpoint-1500/random_states_0.pkl
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checkpoint-1500/scaler.pt
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checkpoint-1500/scheduler.bin
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checkpoint-2000/controlnet/config.json
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{
|
2 |
+
"_class_name": "ControlNetModel",
|
3 |
+
"_diffusers_version": "0.28.0.dev0",
|
4 |
+
"act_fn": "silu",
|
5 |
+
"addition_embed_type": "text_time",
|
6 |
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"addition_embed_type_num_heads": 64,
|
7 |
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"addition_time_embed_dim": 256,
|
8 |
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"attention_head_dim": [
|
9 |
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5,
|
10 |
+
10,
|
11 |
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20
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12 |
+
],
|
13 |
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"block_out_channels": [
|
14 |
+
320,
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15 |
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640,
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16 |
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17 |
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],
|
18 |
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"class_embed_type": null,
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"conditioning_channels": 3,
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"conditioning_embedding_out_channels": [
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|
22 |
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32,
|
23 |
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96,
|
24 |
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256
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25 |
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],
|
26 |
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"controlnet_conditioning_channel_order": "rgb",
|
27 |
+
"cross_attention_dim": 2048,
|
28 |
+
"down_block_types": [
|
29 |
+
"DownBlock2D",
|
30 |
+
"CrossAttnDownBlock2D",
|
31 |
+
"CrossAttnDownBlock2D"
|
32 |
+
],
|
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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,
|
39 |
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"in_channels": 4,
|
40 |
+
"layers_per_block": 2,
|
41 |
+
"mid_block_scale_factor": 1,
|
42 |
+
"mid_block_type": "UNetMidBlock2DCrossAttn",
|
43 |
+
"norm_eps": 1e-05,
|
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"norm_num_groups": 32,
|
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"num_attention_heads": null,
|
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"num_class_embeds": null,
|
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"only_cross_attention": false,
|
48 |
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"projection_class_embeddings_input_dim": 2816,
|
49 |
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"resnet_time_scale_shift": "default",
|
50 |
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"transformer_layers_per_block": [
|
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|
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|
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|
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"upcast_attention": null,
|
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"use_linear_projection": true
|
57 |
+
}
|
checkpoint-2000/controlnet/diffusion_pytorch_model.safetensors
ADDED
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checkpoint-2000/optimizer.bin
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checkpoint-2500/controlnet/config.json
ADDED
@@ -0,0 +1,57 @@
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{
|
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|
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"down_block_types": [
|
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"DownBlock2D",
|
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|
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}
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checkpoint-2500/controlnet/diffusion_pytorch_model.safetensors
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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checkpoint-2500/optimizer.bin
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checkpoint-2500/random_states_0.pkl
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checkpoint-2500/scaler.pt
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checkpoint-500/controlnet/config.json
ADDED
@@ -0,0 +1,57 @@
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|
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checkpoint-500/controlnet/diffusion_pytorch_model.safetensors
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checkpoint-500/optimizer.bin
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checkpoint-500/scaler.pt
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checkpoint-500/scheduler.bin
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config.json
ADDED
@@ -0,0 +1,57 @@
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diffusion_pytorch_model.safetensors
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