Hugging Face's logo

Spaces:
kimjy0411
/
virtual_character2
Runtime error

App Files Community
zejunyang commited on
Commit
1be0964
•
1 Parent(s): 27146ed

init

Browse files
Files changed (6) hide show
  1. pretrained_model/sd-vae-ft-mse +0 -1
  2. pretrained_model/sd-vae-ft-mse/.gitattributes +33 -0
  3. pretrained_model/sd-vae-ft-mse/README.md +83 -0
  4. pretrained_model/sd-vae-ft-mse/config.json +29 -0
  5. pretrained_model/sd-vae-ft-mse/diffusion_pytorch_model.bin +3 -0
  6. pretrained_model/sd-vae-ft-mse/diffusion_pytorch_model.safetensors +3 -0
pretrained_model/sd-vae-ft-mse DELETED
@@ -1 +0,0 @@
1
- Subproject commit 31f26fdeee1355a5c34592e401dd41e45d25a493
 
 
pretrained_model/sd-vae-ft-mse/.gitattributes ADDED
@@ -0,0 +1,33 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ *.7z filter=lfs diff=lfs merge=lfs -text
2
+ *.arrow filter=lfs diff=lfs merge=lfs -text
3
+ *.bin filter=lfs diff=lfs merge=lfs -text
4
+ *.bz2 filter=lfs diff=lfs merge=lfs -text
5
+ *.ftz filter=lfs diff=lfs merge=lfs -text
6
+ *.gz filter=lfs diff=lfs merge=lfs -text
7
+ *.h5 filter=lfs diff=lfs merge=lfs -text
8
+ *.joblib filter=lfs diff=lfs merge=lfs -text
9
+ *.lfs.* filter=lfs diff=lfs merge=lfs -text
10
+ *.mlmodel filter=lfs diff=lfs merge=lfs -text
11
+ *.model filter=lfs diff=lfs merge=lfs -text
12
+ *.msgpack filter=lfs diff=lfs merge=lfs -text
13
+ *.npy filter=lfs diff=lfs merge=lfs -text
14
+ *.npz filter=lfs diff=lfs merge=lfs -text
15
+ *.onnx filter=lfs diff=lfs merge=lfs -text
16
+ *.ot filter=lfs diff=lfs merge=lfs -text
17
+ *.parquet filter=lfs diff=lfs merge=lfs -text
18
+ *.pb filter=lfs diff=lfs merge=lfs -text
19
+ *.pickle filter=lfs diff=lfs merge=lfs -text
20
+ *.pkl filter=lfs diff=lfs merge=lfs -text
21
+ *.pt filter=lfs diff=lfs merge=lfs -text
22
+ *.pth filter=lfs diff=lfs merge=lfs -text
23
+ *.rar filter=lfs diff=lfs merge=lfs -text
24
+ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
25
+ *.tar.* filter=lfs diff=lfs merge=lfs -text
26
+ *.tflite filter=lfs diff=lfs merge=lfs -text
27
+ *.tgz filter=lfs diff=lfs merge=lfs -text
28
+ *.wasm filter=lfs diff=lfs merge=lfs -text
29
+ *.xz filter=lfs diff=lfs merge=lfs -text
30
+ *.zip filter=lfs diff=lfs merge=lfs -text
31
+ *.zst filter=lfs diff=lfs merge=lfs -text
32
+ *tfevents* filter=lfs diff=lfs merge=lfs -text
33
+ diffusion_pytorch_model.safetensors filter=lfs diff=lfs merge=lfs -text
pretrained_model/sd-vae-ft-mse/README.md ADDED
@@ -0,0 +1,83 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: mit
3
+ tags:
4
+ - stable-diffusion
5
+ - stable-diffusion-diffusers
6
+ inference: false
7
+ ---
8
+ # Improved Autoencoders
9
+
10
+ ## Utilizing
11
+ These weights are intended to be used with the [🧨 diffusers library](https://github.com/huggingface/diffusers). If you are looking for the model to use with the original [CompVis Stable Diffusion codebase](https://github.com/CompVis/stable-diffusion), [come here](https://huggingface.co/stabilityai/sd-vae-ft-mse-original).
12
+
13
+ #### How to use with 🧨 diffusers
14
+ You can integrate this fine-tuned VAE decoder to your existing `diffusers` workflows, by including a `vae` argument to the `StableDiffusionPipeline`
15
+ ```py
16
+ from diffusers.models import AutoencoderKL
17
+ from diffusers import StableDiffusionPipeline
18
+
19
+ model = "CompVis/stable-diffusion-v1-4"
20
+ vae = AutoencoderKL.from_pretrained("stabilityai/sd-vae-ft-mse")
21
+ pipe = StableDiffusionPipeline.from_pretrained(model, vae=vae)
22
+ ```
23
+
24
+ ## Decoder Finetuning
25
+ We publish two kl-f8 autoencoder versions, finetuned from the original [kl-f8 autoencoder](https://github.com/CompVis/latent-diffusion#pretrained-autoencoding-models) on a 1:1 ratio of [LAION-Aesthetics](https://laion.ai/blog/laion-aesthetics/) and LAION-Humans, an unreleased subset containing only SFW images of humans. The intent was to fine-tune on the Stable Diffusion training set (the autoencoder was originally trained on OpenImages) but also enrich the dataset with images of humans to improve the reconstruction of faces.
26
+ The first, _ft-EMA_, was resumed from the original checkpoint, trained for 313198 steps and uses EMA weights. It uses the same loss configuration as the original checkpoint (L1 + LPIPS).
27
+ The second, _ft-MSE_, was resumed from _ft-EMA_ and uses EMA weights and was trained for another 280k steps using a different loss, with more emphasis
28
+ on MSE reconstruction (MSE + 0.1 * LPIPS). It produces somewhat ``smoother'' outputs. The batch size for both versions was 192 (16 A100s, batch size 12 per GPU).
29
+ To keep compatibility with existing models, only the decoder part was finetuned; the checkpoints can be used as a drop-in replacement for the existing autoencoder.
30
+
31
+ _Original kl-f8 VAE vs f8-ft-EMA vs f8-ft-MSE_
32
+
33
+ ## Evaluation
34
+ ### COCO 2017 (256x256, val, 5000 images)
35
+ | Model | train steps | rFID | PSNR | SSIM | PSIM | Link | Comments
36
+ |----------|---------|------|--------------|---------------|---------------|-----------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------|
37
+ | | | | | | | | |
38
+ | original | 246803 | 4.99 | 23.4 +/- 3.8 | 0.69 +/- 0.14 | 1.01 +/- 0.28 | https://ommer-lab.com/files/latent-diffusion/kl-f8.zip | as used in SD |
39
+ | ft-EMA | 560001 | 4.42 | 23.8 +/- 3.9 | 0.69 +/- 0.13 | 0.96 +/- 0.27 | https://huggingface.co/stabilityai/sd-vae-ft-ema-original/resolve/main/vae-ft-ema-560000-ema-pruned.ckpt | slightly better overall, with EMA |
40
+ | ft-MSE | 840001 | 4.70 | 24.5 +/- 3.7 | 0.71 +/- 0.13 | 0.92 +/- 0.27 | https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt | resumed with EMA from ft-EMA, emphasis on MSE (rec. loss = MSE + 0.1 * LPIPS), smoother outputs |
41
+
42
+
43
+ ### LAION-Aesthetics 5+ (256x256, subset, 10000 images)
44
+ | Model | train steps | rFID | PSNR | SSIM | PSIM | Link | Comments
45
+ |----------|-----------|------|--------------|---------------|---------------|-----------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------|
46
+ | | | | | | | | |
47
+ | original | 246803 | 2.61 | 26.0 +/- 4.4 | 0.81 +/- 0.12 | 0.75 +/- 0.36 | https://ommer-lab.com/files/latent-diffusion/kl-f8.zip | as used in SD |
48
+ | ft-EMA | 560001 | 1.77 | 26.7 +/- 4.8 | 0.82 +/- 0.12 | 0.67 +/- 0.34 | https://huggingface.co/stabilityai/sd-vae-ft-ema-original/resolve/main/vae-ft-ema-560000-ema-pruned.ckpt | slightly better overall, with EMA |
49
+ | ft-MSE | 840001 | 1.88 | 27.3 +/- 4.7 | 0.83 +/- 0.11 | 0.65 +/- 0.34 | https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt | resumed with EMA from ft-EMA, emphasis on MSE (rec. loss = MSE + 0.1 * LPIPS), smoother outputs |
50
+
51
+
52
+ ### Visual
53
+ _Visualization of reconstructions on 256x256 images from the COCO2017 validation dataset._
54
+
55
+ <p align="center">
56
+ <br>
57
+ <b>
58
+ 256x256: ft-EMA (left), ft-MSE (middle), original (right)</b>
59
+ </p>
60
+
61
+ <p align="center">
62
+ <img src=https://huggingface.co/stabilityai/stable-diffusion-decoder-finetune/resolve/main/eval/ae-decoder-tuning-reconstructions/merged/00025_merged.png />
63
+ </p>
64
+
65
+ <p align="center">
66
+ <img src=https://huggingface.co/stabilityai/stable-diffusion-decoder-finetune/resolve/main/eval/ae-decoder-tuning-reconstructions/merged/00011_merged.png />
67
+ </p>
68
+
69
+ <p align="center">
70
+ <img src=https://huggingface.co/stabilityai/stable-diffusion-decoder-finetune/resolve/main/eval/ae-decoder-tuning-reconstructions/merged/00037_merged.png />
71
+ </p>
72
+
73
+ <p align="center">
74
+ <img src=https://huggingface.co/stabilityai/stable-diffusion-decoder-finetune/resolve/main/eval/ae-decoder-tuning-reconstructions/merged/00043_merged.png />
75
+ </p>
76
+
77
+ <p align="center">
78
+ <img src=https://huggingface.co/stabilityai/stable-diffusion-decoder-finetune/resolve/main/eval/ae-decoder-tuning-reconstructions/merged/00053_merged.png />
79
+ </p>
80
+
81
+ <p align="center">
82
+ <img src=https://huggingface.co/stabilityai/stable-diffusion-decoder-finetune/resolve/main/eval/ae-decoder-tuning-reconstructions/merged/00029_merged.png />
83
+ </p>
pretrained_model/sd-vae-ft-mse/config.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_class_name": "AutoencoderKL",
3
+ "_diffusers_version": "0.4.2",
4
+ "act_fn": "silu",
5
+ "block_out_channels": [
6
+ 128,
7
+ 256,
8
+ 512,
9
+ 512
10
+ ],
11
+ "down_block_types": [
12
+ "DownEncoderBlock2D",
13
+ "DownEncoderBlock2D",
14
+ "DownEncoderBlock2D",
15
+ "DownEncoderBlock2D"
16
+ ],
17
+ "in_channels": 3,
18
+ "latent_channels": 4,
19
+ "layers_per_block": 2,
20
+ "norm_num_groups": 32,
21
+ "out_channels": 3,
22
+ "sample_size": 256,
23
+ "up_block_types": [
24
+ "UpDecoderBlock2D",
25
+ "UpDecoderBlock2D",
26
+ "UpDecoderBlock2D",
27
+ "UpDecoderBlock2D"
28
+ ]
29
+ }
pretrained_model/sd-vae-ft-mse/diffusion_pytorch_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1b4889b6b1d4ce7ae320a02dedaeff1780ad77d415ea0d744b476155c6377ddc
3
+ size 334707217
pretrained_model/sd-vae-ft-mse/diffusion_pytorch_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a1d993488569e928462932c8c38a0760b874d166399b14414135bd9c42df5815
3
+ size 334643276