Publish model
Browse files- README.md +53 -1
- feature_extractor/preprocessor_config.json +20 -0
- model_index.json +33 -0
- scheduler/scheduler_config.json +15 -0
- text_encoder/config.json +25 -0
- text_encoder/pytorch_model.bin +3 -0
- tokenizer/merges.txt +0 -0
- tokenizer/special_tokens_map.json +24 -0
- tokenizer/tokenizer_config.json +34 -0
- tokenizer/vocab.json +0 -0
- unet/config.json +45 -0
- unet/diffusion_pytorch_model.bin +3 -0
- vae/config.json +29 -0
- vae/diffusion_pytorch_model.bin +3 -0
README.md
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---
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-
license: openrail
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---
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---
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license: openrail++
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tags:
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- stable-diffusion
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- text-to-image
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---
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# SD v2.1-base with Self-Perceptual Objective
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This is the official model in [Diffusion Model with Perceptual Loss](https://arxiv.org/abs/2401.00110) paper.
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This model is trained using the self-perceptual objective. It no longer needs classifier-free guidance to produce sensible images.
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This model is trained using zero terminal SNR schedule following [Common Diffusion Noise Schedules and Sample Steps are Flawed](https://arxiv.org/abs/2305.08891) paper on LAION aesthetic 6+ data.
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This model is finetuned from [stabilityai/stable-diffusion-2-1-base](https://huggingface.co/stabilityai/stable-diffusion-2-1-base).
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This model is meant for research demonstration, not for production use.
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## Usage
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```python
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from diffusers import StableDiffusionPipeline
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prompt = "A young girl smiling"
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pipe = StableDiffusionPipeline.from_pretrained("ByteDance/sd2.1-base-zsnr-laionaes6-perceptual").to("cuda")
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pipe(prompt, guidance_scale=0).images[0].save("out.jpg") # No need for CFG!
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```
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## Related Models
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* [bytedance/sd2.1-base-zsnr-laionaes5](https://huggingface.co/ByteDance/sd2.1-base-zsnr-laionaes5)
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* [bytedance/sd2.1-base-zsnr-laionaes6](https://huggingface.co/ByteDance/sd2.1-base-zsnr-laionaes6)
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* [bytedance/sd2.1-base-zsnr-laionaes6-perceptual](https://huggingface.co/ByteDance/sd2.1-base-zsnr-laionaes6-perceptual)
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## Cite as
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```
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@misc{lin2024diffusion,
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title={Diffusion Model with Perceptual Loss},
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author={Shanchuan Lin and Xiao Yang},
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year={2024},
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eprint={2401.00110},
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archivePrefix={arXiv},
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primaryClass={cs.CV}
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}
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@misc{lin2023common,
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title={Common Diffusion Noise Schedules and Sample Steps are Flawed},
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author={Shanchuan Lin and Bingchen Liu and Jiashi Li and Xiao Yang},
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year={2023},
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eprint={2305.08891},
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archivePrefix={arXiv},
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primaryClass={cs.CV}
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}
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```
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feature_extractor/preprocessor_config.json
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{
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"crop_size": 224,
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"do_center_crop": true,
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"do_convert_rgb": true,
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"do_normalize": true,
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"do_resize": true,
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"feature_extractor_type": "CLIPFeatureExtractor",
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"image_mean": [
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0.48145466,
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0.4578275,
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0.40821073
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],
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"image_std": [
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0.26862954,
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0.26130258,
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0.27577711
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],
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"resample": 3,
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"size": 224
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}
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model_index.json
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{
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"_class_name": "StableDiffusionPipeline",
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"_diffusers_version": "0.23.1",
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"feature_extractor": [
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"transformers",
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"CLIPImageProcessor"
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],
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"requires_safety_checker": false,
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"safety_checker": [
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null,
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null
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],
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"scheduler": [
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"diffusers",
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"DDIMScheduler"
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],
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"text_encoder": [
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"transformers",
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"CLIPTextModel"
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],
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"tokenizer": [
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"transformers",
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"CLIPTokenizer"
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],
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"unet": [
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"diffusers",
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"UNet2DConditionModel"
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],
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"vae": [
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"diffusers",
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"AutoencoderKL"
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]
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}
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scheduler/scheduler_config.json
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{
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"_class_name": "DDIMScheduler",
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"_diffusers_version": "0.23.1",
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"beta_end": 0.012,
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"beta_schedule": "scaled_linear",
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"beta_start": 0.00085,
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"clip_sample": false,
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"num_train_timesteps": 1000,
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"prediction_type": "v_prediction",
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"set_alpha_to_one": true,
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"steps_offset": 1,
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"trained_betas": null,
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"timestep_spacing": "trailing",
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"rescale_betas_zero_snr": true
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}
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text_encoder/config.json
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{
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"_name_or_path": "stabilityai/stable-diffusion-2",
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"architectures": [
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"CLIPTextModel"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 0,
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"dropout": 0.0,
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"eos_token_id": 2,
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"hidden_act": "gelu",
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"hidden_size": 1024,
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"initializer_factor": 1.0,
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 77,
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"model_type": "clip_text_model",
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"num_attention_heads": 16,
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"num_hidden_layers": 23,
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"pad_token_id": 1,
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"projection_dim": 512,
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"torch_dtype": "float32",
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"transformers_version": "4.25.0.dev0",
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"vocab_size": 49408
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}
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text_encoder/pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:c3e254d7b61353497ea0be2c4013df4ea8f739ee88cffa0ba58cd085459ed565
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size 1361671895
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tokenizer/merges.txt
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tokenizer/special_tokens_map.json
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{
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"bos_token": {
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"content": "<|startoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": "!",
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"unk_token": {
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer/tokenizer_config.json
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{
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"add_prefix_space": false,
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"bos_token": {
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"__type": "AddedToken",
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"content": "<|startoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"do_lower_case": true,
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"eos_token": {
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"__type": "AddedToken",
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
|
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+
"errors": "replace",
|
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+
"model_max_length": 77,
|
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+
"name_or_path": "stabilityai/stable-diffusion-2",
|
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+
"pad_token": "<|endoftext|>",
|
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+
"special_tokens_map_file": "./special_tokens_map.json",
|
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"tokenizer_class": "CLIPTokenizer",
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+
"unk_token": {
|
27 |
+
"__type": "AddedToken",
|
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+
"content": "<|endoftext|>",
|
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+
"lstrip": false,
|
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+
"normalized": true,
|
31 |
+
"rstrip": false,
|
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"single_word": false
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}
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}
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tokenizer/vocab.json
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unet/config.json
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{
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"_class_name": "UNet2DConditionModel",
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"_diffusers_version": "0.10.0.dev0",
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"act_fn": "silu",
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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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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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1280
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],
|
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"center_input_sample": false,
|
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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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+
"dual_cross_attention": false,
|
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+
"flip_sin_to_cos": true,
|
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+
"freq_shift": 0,
|
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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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+
"norm_eps": 1e-05,
|
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+
"norm_num_groups": 32,
|
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+
"num_class_embeds": null,
|
35 |
+
"only_cross_attention": false,
|
36 |
+
"out_channels": 4,
|
37 |
+
"sample_size": 64,
|
38 |
+
"up_block_types": [
|
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+
"UpBlock2D",
|
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+
"CrossAttnUpBlock2D",
|
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+
"CrossAttnUpBlock2D",
|
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+
"CrossAttnUpBlock2D"
|
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+
],
|
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+
"use_linear_projection": true
|
45 |
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}
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unet/diffusion_pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:d51403065b0bcdf87205776a0acb115781e5a6719f93f1b7440d264b51f85b43
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size 3463925434
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vae/config.json
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{
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"_class_name": "AutoencoderKL",
|
3 |
+
"_diffusers_version": "0.10.0.dev0",
|
4 |
+
"act_fn": "silu",
|
5 |
+
"block_out_channels": [
|
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128,
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7 |
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256,
|
8 |
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512,
|
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+
512
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],
|
11 |
+
"down_block_types": [
|
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+
"DownEncoderBlock2D",
|
13 |
+
"DownEncoderBlock2D",
|
14 |
+
"DownEncoderBlock2D",
|
15 |
+
"DownEncoderBlock2D"
|
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+
],
|
17 |
+
"in_channels": 3,
|
18 |
+
"latent_channels": 4,
|
19 |
+
"layers_per_block": 2,
|
20 |
+
"norm_num_groups": 32,
|
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+
"out_channels": 3,
|
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+
"sample_size": 768,
|
23 |
+
"up_block_types": [
|
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"UpDecoderBlock2D",
|
25 |
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"UpDecoderBlock2D",
|
26 |
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"UpDecoderBlock2D",
|
27 |
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"UpDecoderBlock2D"
|
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]
|
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}
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vae/diffusion_pytorch_model.bin
ADDED
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+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:1b4889b6b1d4ce7ae320a02dedaeff1780ad77d415ea0d744b476155c6377ddc
|
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+
size 334707217
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