strangeman3107
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Browse files- .gitattributes +3 -0
- README.md +5 -0
- model_index.json +24 -0
- scheduler/scheduler_config.json +18 -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 +33 -0
- tokenizer/vocab.json +0 -0
- unet/config.json +34 -0
- unet/diffusion_pytorch_model.bin +3 -0
- vae/config.json +31 -0
- vae/diffusion_pytorch_model.bin +3 -0
.gitattributes
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text_encoder/pytorch_model.bin filter=lfs diff=lfs merge=lfs -text
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unet/diffusion_pytorch_model.bin filter=lfs diff=lfs merge=lfs -text
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vae/diffusion_pytorch_model.bin filter=lfs diff=lfs merge=lfs -text
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README.md
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This is a text2video model for diffusers, fine-tuned with a [modelscope](https://huggingface.co/damo-vilab/text-to-video-ms-1.7b) to have an anime-style appearance.
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It was trained at 448x384 resolution.
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The usage is the same as with the original modelscope model.
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The main difference from version 0.1 is only the resolution.
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model_index.json
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{
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"_class_name": "TextToVideoSDPipeline",
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"_diffusers_version": "0.15.0.dev0",
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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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"UNet3DConditionModel"
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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": "0.15.0.dev0",
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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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"clip_sample_range": 1.0,
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"dynamic_thresholding_ratio": 0.995,
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"num_train_timesteps": 1000,
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"prediction_type": "epsilon",
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"sample_max_value": 1.0,
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"set_alpha_to_one": false,
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"skip_prk_steps": true,
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"steps_offset": 1,
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"thresholding": false,
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"trained_betas": null
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}
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text_encoder/config.json
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{
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"_name_or_path": "./models/model_scope_diffusers/",
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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": "float16",
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"transformers_version": "4.27.3",
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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:b7c89ba5773b9b5c11b57f676c658047bd2d7c31c207acde13d06d7951101b0b
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size 680904225
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tokenizer/merges.txt
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The diff for this file is too large to render.
See raw diff
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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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"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": {
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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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}
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tokenizer/vocab.json
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The diff for this file is too large to render.
See raw diff
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unet/config.json
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{
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"_class_name": "UNet3DConditionModel",
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"_diffusers_version": "0.15.0.dev0",
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"_name_or_path": "./models/model_scope_diffusers/",
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"act_fn": "silu",
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"attention_head_dim": 64,
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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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"cross_attention_dim": 1024,
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"down_block_types": [
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"CrossAttnDownBlock3D",
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"CrossAttnDownBlock3D",
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"CrossAttnDownBlock3D",
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"DownBlock3D"
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],
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"downsample_padding": 1,
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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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"out_channels": 4,
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"sample_size": 32,
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"up_block_types": [
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"UpBlock3D",
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"CrossAttnUpBlock3D",
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"CrossAttnUpBlock3D",
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"CrossAttnUpBlock3D"
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]
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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 sha256:426c0b7df5e676185cabcc7adf467a46c63bb57029a9e91b98c59af3d032f2b0
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size 2823110385
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vae/config.json
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{
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"_class_name": "AutoencoderKL",
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"_diffusers_version": "0.15.0.dev0",
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"_name_or_path": "./models/model_scope_diffusers/",
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"act_fn": "silu",
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"block_out_channels": [
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128,
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256,
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512,
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512
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],
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"down_block_types": [
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"DownEncoderBlock2D",
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"DownEncoderBlock2D",
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"DownEncoderBlock2D",
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"DownEncoderBlock2D"
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],
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"in_channels": 3,
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"latent_channels": 4,
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"layers_per_block": 2,
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"norm_num_groups": 32,
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"out_channels": 3,
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"sample_size": 512,
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"scaling_factor": 0.18215,
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"up_block_types": [
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"UpDecoderBlock2D",
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"UpDecoderBlock2D",
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"UpDecoderBlock2D",
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"UpDecoderBlock2D"
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]
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}
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vae/diffusion_pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:cb475c1672d6273bafae618c8de499f383476fc692795c9d0abc97c6b87f1058
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size 167407601
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