c50de26eff056d7a06266208b76d2388ccfe8377ed012eab097011adf37d79de
Browse files- safety_checker/pytorch_model.bin +3 -0
- scheduler/scheduler_config.json +21 -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 +40 -0
- v1-inference.yaml +70 -0
- vae/config.json +29 -0
- vae/diffusion_pytorch_model.bin +3 -0
safety_checker/pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:16d28f2b37109f222cdc33620fdd262102ac32112be0352a7f77e9614b35a394
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size 1216064769
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scheduler/scheduler_config.json
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{
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"_class_name": "DPMSolverMultistepScheduler",
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"_diffusers_version": "0.10.0",
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"algorithm_type": "dpmsolver++",
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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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"dynamic_thresholding_ratio": 0.995,
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"lower_order_final": true,
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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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"solver_order": 2,
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"solver_type": "midpoint",
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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": "openai/clip-vit-large-patch14",
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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": "quick_gelu",
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"hidden_size": 768,
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"initializer_factor": 1.0,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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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": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 1,
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"projection_dim": 768,
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"torch_dtype": "float32",
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"transformers_version": "4.26.0.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:f3ab84100c78aa0ea459336509d08ca3ecb2df5325b1aae35189d080326f5ab9
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size 492307041
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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": "<|endoftext|>",
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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": "openai/clip-vit-large-patch14",
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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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unet/config.json
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{
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"_class_name": "UNet2DConditionModel",
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"_diffusers_version": "0.11.0.dev0",
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"act_fn": "silu",
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"attention_head_dim": 8,
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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": 768,
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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,
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"only_cross_attention": false,
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"out_channels": 4,
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"sample_size": 64,
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"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": false
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}
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v1-inference.yaml
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model:
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base_learning_rate: 1.0e-04
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target: ldm.models.diffusion.ddpm.LatentDiffusion
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params:
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linear_start: 0.00085
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linear_end: 0.0120
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num_timesteps_cond: 1
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log_every_t: 200
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timesteps: 1000
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first_stage_key: "jpg"
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cond_stage_key: "txt"
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image_size: 64
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channels: 4
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cond_stage_trainable: false # Note: different from the one we trained before
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conditioning_key: crossattn
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monitor: val/loss_simple_ema
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scale_factor: 0.18215
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use_ema: False
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scheduler_config: # 10000 warmup steps
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target: ldm.lr_scheduler.LambdaLinearScheduler
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params:
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warm_up_steps: [ 10000 ]
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cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
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f_start: [ 1.e-6 ]
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f_max: [ 1. ]
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f_min: [ 1. ]
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unet_config:
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target: ldm.modules.diffusionmodules.openaimodel.UNetModel
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params:
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image_size: 32 # unused
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in_channels: 4
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out_channels: 4
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model_channels: 320
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attention_resolutions: [ 4, 2, 1 ]
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num_res_blocks: 2
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channel_mult: [ 1, 2, 4, 4 ]
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num_heads: 8
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use_spatial_transformer: True
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transformer_depth: 1
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context_dim: 768
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use_checkpoint: True
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legacy: False
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first_stage_config:
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target: ldm.models.autoencoder.AutoencoderKL
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params:
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embed_dim: 4
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monitor: val/rec_loss
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ddconfig:
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double_z: true
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z_channels: 4
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resolution: 256
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in_channels: 3
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out_ch: 3
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ch: 128
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ch_mult:
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- 1
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- 2
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- 4
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- 4
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num_res_blocks: 2
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attn_resolutions: []
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dropout: 0.0
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lossconfig:
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target: torch.nn.Identity
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cond_stage_config:
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target: ldm.modules.encoders.modules.FrozenCLIPEmbedder
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vae/config.json
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{
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"_class_name": "AutoencoderKL",
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"_diffusers_version": "0.4.2",
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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": 256,
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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 sha256:7c98ebcd7ca5cb69d47b2ae287feba0695689fbf2c8fead2fab05fd3e0c28303
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3 |
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size 334707217
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