upload

README.md

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+---
+license: mit
+---
+
+Upload zero123-xl.ckpt, converted by diffusers scripts convert_original_stable_diffusion_to_diffusers.py
+
+[Zero123-hf](https://github.com/kxhit/zero123_hf) implemented with diffusers pipelines.
+
+Thanks Original Repo [Zero123](https://github.com/cvlab-columbia/zero123), and [Weights](https://huggingface.co/cvlab/zero123-weights).

cc_projection/config.json

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+  "_class_name": "ProjectionModel",
+  "_diffusers_version": "0.18.2",
+  "in_channels": 772,
+  "out_channels": 768
+}

cc_projection/diffusion_pytorch_model.bin

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feature_extractor/preprocessor_config.json

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+    "width": 224
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+  "do_center_crop": true,
+  "do_convert_rgb": true,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "feature_extractor_type": "CLIPFeatureExtractor",
+  "image_mean": [
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+    0.4578275,
+    0.40821073
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+  "image_processor_type": "CLIPImageProcessor",
+  "image_std": [
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+  "resample": 3,
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+  "size": {
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+}

image_encoder/config.json

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+  "architectures": [
+    "CLIPVisionModelWithProjection"
+  ],
+  "attention_dropout": 0.0,
+  "dropout": 0.0,
+  "hidden_act": "quick_gelu",
+  "hidden_size": 1024,
+  "image_size": 224,
+  "initializer_factor": 1.0,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-05,
+  "model_type": "clip_vision_model",
+  "num_attention_heads": 16,
+  "num_channels": 3,
+  "num_hidden_layers": 24,
+  "patch_size": 14,
+  "projection_dim": 768,
+  "torch_dtype": "float32",
+  "transformers_version": "4.25.1"
+}

image_encoder/pytorch_model.bin

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model_index.json

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+{
+  "_class_name": "StableDiffusionPipeline",
+  "_diffusers_version": "0.18.2",
+  "feature_extractor": [
+    "transformers",
+    "CLIPFeatureExtractor"
+  ],
+  "requires_safety_checker": true,
+  "safety_checker": [
+    "stable_diffusion",
+    "StableDiffusionSafetyChecker"
+  ],
+  "scheduler": [
+    "diffusers",
+    "PNDMScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "CLIPTextModel"
+  ],
+  "tokenizer": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "unet": [
+    "diffusers",
+    "UNet2DConditionModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}

safety_checker/config.json

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safety_checker/pytorch_model.bin

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scheduler/scheduler_config.json

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text_encoder/config.json

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tokenizer/special_tokens_map.json

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tokenizer/tokenizer_config.json

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unet/config.json

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vae/config.json

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