pyx9913 commited on
Commit
b8b90d5
1 Parent(s): 3fbf51c

update ckpt

Browse files
README.md CHANGED
@@ -41,7 +41,7 @@ from transformers import AutoTokenizer
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  tokenizer = AutoTokenizer.from_pretrained('openbmb/VisCPM-Paint', trust_remote_code=True)
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  text_encoder = AutoModel.from_pretrained('openbmb/VisCPM-Paint', trust_remote_code=True)
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  print('load pipeline')
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- pipeline = DiffusionPipeline.from_pretrained('openbmb/VisCPM-Paint', custom_pipeline="pipeline_stable_diffusion.py", text_encoder=text_encoder, tokenizer=tokenizer)
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  pipeline = pipeline.to('cuda')
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  tokenizer = AutoTokenizer.from_pretrained('openbmb/VisCPM-Paint', trust_remote_code=True)
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  text_encoder = AutoModel.from_pretrained('openbmb/VisCPM-Paint', trust_remote_code=True)
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  print('load pipeline')
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+ pipeline = DiffusionPipeline.from_pretrained('openbmb/VisCPM-Paint', custom_pipeline="openbmb/VisCPM-Paint", text_encoder=text_encoder, tokenizer=tokenizer)
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  pipeline = pipeline.to('cuda')
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scheduler/scheduler_config.json CHANGED
@@ -1,10 +1,11 @@
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  {
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- "_class_name": "DDIMScheduler",
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- "_diffusers_version": "0.8.0",
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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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  "clip_sample": false,
 
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  "num_train_timesteps": 1000,
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  "prediction_type": "epsilon",
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  "set_alpha_to_one": false,
 
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  {
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+ "_class_name": "EulerDiscreteScheduler",
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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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+ "interpolation_type": "linear",
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  "num_train_timesteps": 1000,
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  "prediction_type": "epsilon",
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  "set_alpha_to_one": false,
unet/config.json CHANGED
@@ -1,6 +1,7 @@
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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,
@@ -15,6 +16,10 @@
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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",
@@ -29,17 +34,24 @@
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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": true
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  }
 
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  {
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  "_class_name": "UNet2DConditionModel",
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+ "_diffusers_version": "0.15.0.dev0",
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+ "_name_or_path": "/home/jeeves/checkpoints/stable-diffution-v2-1/v1_20230103/snapshots/88bb1a46821197d1ac0cb54d1d09fb6e70b171bc/unet",
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  "act_fn": "silu",
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  "attention_head_dim": [
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  5,
 
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  1280
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  ],
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  "center_input_sample": false,
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+ "class_embed_type": null,
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+ "class_embeddings_concat": false,
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+ "conv_in_kernel": 3,
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+ "conv_out_kernel": 3,
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  "cross_attention_dim": 1024,
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  "down_block_types": [
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  "CrossAttnDownBlock2D",
 
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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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+ "mid_block_type": "UNetMidBlock2DCrossAttn",
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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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+ "projection_class_embeddings_input_dim": null,
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+ "resnet_time_scale_shift": "default",
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  "sample_size": 64,
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+ "time_cond_proj_dim": null,
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+ "time_embedding_type": "positional",
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+ "timestep_post_act": null,
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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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+ "upcast_attention": false,
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  "use_linear_projection": true
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  }
unet/diffusion_pytorch_model.balance.bin ADDED
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unet/diffusion_pytorch_model.bin ADDED
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vae/config.json CHANGED
@@ -1,6 +1,7 @@
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  {
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  "_class_name": "AutoencoderKL",
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- "_diffusers_version": "0.8.0",
 
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  "act_fn": "silu",
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  "block_out_channels": [
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  128,
@@ -20,6 +21,7 @@
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  "norm_num_groups": 32,
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  "out_channels": 3,
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  "sample_size": 768,
 
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  "up_block_types": [
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  "UpDecoderBlock2D",
 
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+ "_diffusers_version": "0.15.0.dev0",
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+ "_name_or_path": "/home/jeeves/checkpoints/stable-diffution-v2-1/v1_20230103/snapshots/88bb1a46821197d1ac0cb54d1d09fb6e70b171bc/vae",
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  "act_fn": "silu",
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  "block_out_channels": [
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  128,
 
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  "norm_num_groups": 32,
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  "out_channels": 3,
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  "sample_size": 768,
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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",
vae/diffusion_pytorch_model.bin ADDED
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