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End of training

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README.md ADDED
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+
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+ ---
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+ tags:
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+ - autotrain
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+ - stable-diffusion
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+ - stable-diffusion-diffusers
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+ - text-to-image
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+ - diffusers
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+ - lora
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+ - template:sd-lora
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+
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+ base_model: runwayml/stable-diffusion-v1-5
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+ instance_prompt: a cartoon drawing of
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+ license: openrail++
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+ ---
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+
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+ # AutoTrain LoRA DreamBooth - elchileno/bad
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+
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+ These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were trained on a cartoon drawing of using [DreamBooth](https://dreambooth.github.io/).
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+ LoRA for the text encoder was enabled: False.
prompt.txt ADDED
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+ a cartoon drawing of
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training_params.json ADDED
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+ {"model": "runwayml/stable-diffusion-v1-5", "vae_model": "madebyollin/sdxl-vae-fp16-fix", "revision": null, "tokenizer": null, "image_path": "bad/autotrain-data", "class_image_path": null, "prompt": "a cartoon drawing of", "class_prompt": null, "num_class_images": 100, "class_labels_conditioning": null, "prior_preservation": false, "prior_loss_weight": 1.0, "project_name": "bad", "seed": 42, "resolution": 512, "center_crop": false, "train_text_encoder": false, "batch_size": 1, "sample_batch_size": 4, "epochs": 1, "num_steps": 250, "checkpointing_steps": 500, "resume_from_checkpoint": null, "gradient_accumulation": 4, "disable_gradient_checkpointing": false, "lr": 0.0001, "scale_lr": false, "scheduler": "constant", "warmup_steps": 0, "num_cycles": 1, "lr_power": 1.0, "dataloader_num_workers": 0, "use_8bit_adam": false, "adam_beta1": 0.9, "adam_beta2": 0.999, "adam_weight_decay": 0.01, "adam_epsilon": 1e-08, "max_grad_norm": 1.0, "allow_tf32": false, "prior_generation_precision": null, "local_rank": -1, "xformers": false, "pre_compute_text_embeddings": false, "tokenizer_max_length": null, "text_encoder_use_attention_mask": false, "rank": 4, "xl": false, "mixed_precision": "fp16", "repo_id": "elchileno/bad", "push_to_hub": true, "username": "elchileno", "validation_prompt": null, "num_validation_images": 4, "validation_epochs": 50, "checkpoints_total_limit": null, "validation_images": null, "logging": false}