End of training

README.md

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+
+---
+license: creativeml-openrail-m
+base_model: stabilityai/stable-diffusion-2-1
+tags:
+- stable-diffusion
+- stable-diffusion-diffusers
+- text-to-image
+- diffusers
+- textual_inversion
+inference: true
+---
+    
+# Textual inversion text2image fine-tuning - briannlongzhao/church_textual_inversion
+These are textual inversion adaption weights for stabilityai/stable-diffusion-2-1. You can find some example images in the following. 
+
+

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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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+  "image_processor_type": "CLIPImageProcessor",
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logs/textual_inversion/1698968922.418273/hparams.yml

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+adam_beta1: 0.9
+adam_beta2: 0.999
+adam_epsilon: 1.0e-08
+adam_weight_decay: 0.01
+allow_tf32: false
+center_crop: false
+checkpointing_steps: 500
+checkpoints_total_limit: null
+dataloader_num_workers: 0
+enable_xformers_memory_efficient_attention: true
+gradient_accumulation_steps: 4
+gradient_checkpointing: false
+hub_model_id: null
+hub_token: null
+initializer_token: church
+learnable_property: object
+learning_rate: 0.002
+local_rank: 0
+logging_dir: logs
+lr_num_cycles: 1
+lr_scheduler: constant
+lr_warmup_steps: 0
+max_train_steps: 3000
+mixed_precision: fp16
+no_safe_serialization: false
+num_train_epochs: 9
+num_validation_images: 4
+num_vectors: 1
+output_dir: /home/v-enlongzhao/sdcoop-images/models/church_textual_inversion
+placeholder_token: <church>
+pretrained_model_name_or_path: stabilityai/stable-diffusion-2-1
+push_to_hub: true
+repeats: 100
+report_to: tensorboard
+resolution: 768
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+save_steps: 500
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+seed: null
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+train_data_dir: /home/v-enlongzhao/sdcoop-images/images/church
+validation_epochs: null
+validation_prompt: null
+validation_steps: 100

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model_index.json

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+  "_diffusers_version": "0.22.0.dev0",
+  "_name_or_path": "stabilityai/stable-diffusion-2-1",
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+  ]
+}

scheduler/scheduler_config.json

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text_encoder/config.json

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+  "torch_dtype": "float32",
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tokenizer/added_tokens.json

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tokenizer/special_tokens_map.json

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tokenizer/tokenizer_config.json

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+}