add dummy
Browse files- README.md +4 -0
- feature_extractor/preprocessor_config.json +27 -0
- image_encoder/config.json +21 -0
- image_encoder/pytorch_model.bin +3 -0
- model_index.json +24 -0
- scheduler/scheduler_config.json +18 -0
- unet/config.json +26 -0
- unet/diffusion_pytorch_model.bin +3 -0
- vae/config.json +19 -0
- vae/diffusion_pytorch_model.bin +3 -0
README.md
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---
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license: mit
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---
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license: mit
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This is random dummy model for stable video diffusion inspired by the [test script](https://github.com/huggingface/diffusers/blob/main/tests/pipelines/stable_video_diffusion/test_stable_video_diffusion.py) in the diffusers library (script for creating the repo [here](https://github.com/JingyaHuang/neuron-playground/blob/main/stable_diffusion/utils/dummy_sd_video.py)).
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This model aims for internal testing, please do not use it in other scenarios.
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feature_extractor/preprocessor_config.json
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{
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"crop_size": {
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"height": 32,
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"width": 32
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},
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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_rescale": true,
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"do_resize": true,
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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_processor_type": "CLIPImageProcessor",
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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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"rescale_factor": 0.00392156862745098,
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"size": {
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"shortest_edge": 32
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}
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}
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image_encoder/config.json
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{
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"architectures": [
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"CLIPVisionModelWithProjection"
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],
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"attention_dropout": 0.0,
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"hidden_act": "quick_gelu",
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"hidden_size": 32,
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"image_size": 32,
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"initializer_factor": 1.0,
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"initializer_range": 0.02,
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"intermediate_size": 37,
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"layer_norm_eps": 1e-05,
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"model_type": "clip_vision_model",
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"num_attention_heads": 4,
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"num_channels": 3,
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"num_hidden_layers": 5,
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"patch_size": 1,
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"projection_dim": 32,
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"torch_dtype": "float32",
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"transformers_version": "4.36.2"
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}
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image_encoder/pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:bf3d19058d12326e930c1086726f37574aa0918081c2fabac94ec922c7dd7765
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size 300409
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model_index.json
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{
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"_class_name": "StableVideoDiffusionPipeline",
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"_diffusers_version": "0.25.0",
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"feature_extractor": [
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"transformers",
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"CLIPImageProcessor"
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],
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"image_encoder": [
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"transformers",
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"CLIPVisionModelWithProjection"
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],
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"scheduler": [
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"diffusers",
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"EulerDiscreteScheduler"
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],
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"unet": [
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"diffusers",
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"UNetSpatioTemporalConditionModel"
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],
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"vae": [
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"diffusers",
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"AutoencoderKLTemporalDecoder"
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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": "EulerDiscreteScheduler",
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"_diffusers_version": "0.25.0",
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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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"interpolation_type": "linear",
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"num_train_timesteps": 1000,
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"prediction_type": "v_prediction",
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"rescale_betas_zero_snr": false,
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"sigma_max": 700.0,
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"sigma_min": 0.002,
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"steps_offset": 1,
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"timestep_spacing": "leading",
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"timestep_type": "continuous",
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"trained_betas": null,
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"use_karras_sigmas": true
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}
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unet/config.json
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{
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"_class_name": "UNetSpatioTemporalConditionModel",
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"_diffusers_version": "0.25.0",
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"addition_time_embed_dim": 32,
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"block_out_channels": [
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32,
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64
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],
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"cross_attention_dim": 32,
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"down_block_types": [
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"CrossAttnDownBlockSpatioTemporal",
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"DownBlockSpatioTemporal"
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],
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"in_channels": 8,
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"layers_per_block": 2,
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"num_attention_heads": 8,
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"num_frames": 25,
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"out_channels": 4,
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"projection_class_embeddings_input_dim": 96,
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"sample_size": 32,
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"transformer_layers_per_block": 1,
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"up_block_types": [
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"UpBlockSpatioTemporal",
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"CrossAttnUpBlockSpatioTemporal"
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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 sha256:8b398b486e8695b43daed929a046ee76736b7070f728c7dffe10bd6a5f0fbef4
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size 7439581
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vae/config.json
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{
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"_class_name": "AutoencoderKLTemporalDecoder",
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"_diffusers_version": "0.25.0",
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"block_out_channels": [
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32,
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64
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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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],
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"force_upcast": true,
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"in_channels": 3,
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"latent_channels": 4,
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"layers_per_block": 1,
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"out_channels": 3,
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"sample_size": 32,
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"scaling_factor": 0.18215
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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:a798b775cbc6dcd80ebf1a4c320c81bd403523679dbde26a26c7adcd25a03d56
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size 2752239
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