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Upload small random test pipeline for the consistency models EDM implementation (class conditional)

model_index.json

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+{
+  "_class_name": "KarrasEDMPipeline",
+  "_diffusers_version": "0.22.0.dev0",
+  "scheduler": [
+    "diffusers",
+    "KarrasEDMScheduler"
+  ],
+  "unet": [
+    "diffusers",
+    "UNet2DModel"
+  ]
+}

scheduler/scheduler_config.json

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+{
+  "_class_name": "KarrasEDMScheduler",
+  "_diffusers_version": "0.22.0.dev0",
+  "clip_sample": false,
+  "clip_sample_range": 1.0,
+  "num_train_timesteps": 40,
+  "precondition_type": "edm",
+  "prediction_type": "edm",
+  "rho": 7.0,
+  "s_churn": 0.0,
+  "s_noise": 1.0,
+  "s_tmax": Infinity,
+  "s_tmin": 0.0,
+  "sigma_data": 0.5,
+  "sigma_max": 80.0,
+  "sigma_min": 0.002,
+  "timestep_spacing": "linspace"
+}

unet/config.json

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+{
+  "_class_name": "UNet2DModel",
+  "_diffusers_version": "0.22.0.dev0",
+  "act_fn": "silu",
+  "add_attention": true,
+  "attention_head_dim": 8,
+  "attn_norm_num_groups": 32,
+  "block_out_channels": [
+    32,
+    64
+  ],
+  "center_input_sample": false,
+  "class_embed_type": null,
+  "down_block_types": [
+    "ResnetDownsampleBlock2D",
+    "AttnDownBlock2D"
+  ],
+  "downsample_padding": 1,
+  "downsample_type": "resnet",
+  "dropout": 0.0,
+  "flip_sin_to_cos": true,
+  "freq_shift": 0,
+  "in_channels": 3,
+  "layers_per_block": 2,
+  "mid_block_scale_factor": 1,
+  "norm_eps": 1e-05,
+  "norm_num_groups": 32,
+  "num_class_embeds": 1000,
+  "out_channels": 3,
+  "resnet_time_scale_shift": "scale_shift",
+  "sample_size": 32,
+  "time_embedding_type": "positional",
+  "up_block_types": [
+    "AttnUpBlock2D",
+    "ResnetUpsampleBlock2D"
+  ],
+  "upsample_type": "resnet"
+}

unet/diffusion_pytorch_model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:74c24e2a295ea2c52edf3c967ee330cfafa2fef53f82c943dde61a77655dc125
+size 5145572