End of training
Browse files- README.md +40 -0
- checkpoint-1000/optimizer.bin +3 -0
- checkpoint-1000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-1000/random_states_0.pkl +3 -0
- checkpoint-1000/scaler.pt +3 -0
- checkpoint-1000/scheduler.bin +3 -0
- checkpoint-1500/optimizer.bin +3 -0
- checkpoint-1500/pytorch_lora_weights.safetensors +3 -0
- checkpoint-1500/random_states_0.pkl +3 -0
- checkpoint-1500/scaler.pt +3 -0
- checkpoint-1500/scheduler.bin +3 -0
- checkpoint-2000/optimizer.bin +3 -0
- checkpoint-2000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-2000/random_states_0.pkl +3 -0
- checkpoint-2000/scaler.pt +3 -0
- checkpoint-2000/scheduler.bin +3 -0
- checkpoint-2500/optimizer.bin +3 -0
- checkpoint-2500/pytorch_lora_weights.safetensors +3 -0
- checkpoint-2500/random_states_0.pkl +3 -0
- checkpoint-2500/scaler.pt +3 -0
- checkpoint-2500/scheduler.bin +3 -0
- checkpoint-500/optimizer.bin +3 -0
- checkpoint-500/pytorch_lora_weights.safetensors +3 -0
- checkpoint-500/random_states_0.pkl +3 -0
- checkpoint-500/scaler.pt +3 -0
- checkpoint-500/scheduler.bin +3 -0
- prompt.txt +1 -0
- pytorch_lora_weights.safetensors +3 -0
- pytorch_lora_weights_kohya.safetensors +3 -0
- training_params.json +1 -0
README.md
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---
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tags:
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- autotrain
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- stable-diffusion-xl
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- stable-diffusion-xl-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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base_model: stabilityai/sdxl-turbo
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instance_prompt: persik, cat, persik 2d
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license: openrail++
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---
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# AutoTrain SDXL LoRA DreamBooth - adiktus9116/autotrain-s8tkg-fp8ir
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<Gallery />
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## Model description
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These are adiktus9116/autotrain-s8tkg-fp8ir LoRA adaption weights for stabilityai/sdxl-turbo.
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The weights were trained using [DreamBooth](https://dreambooth.github.io/).
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LoRA for the text encoder was enabled: False.
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Special VAE used for training: None.
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## Trigger words
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You should use persik, cat, persik 2d to trigger the image generation.
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## Download model
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Weights for this model are available in Safetensors format.
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[Download](adiktus9116/autotrain-s8tkg-fp8ir/tree/main) them in the Files & versions tab.
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checkpoint-1000/optimizer.bin
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checkpoint-1000/pytorch_lora_weights.safetensors
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checkpoint-1000/random_states_0.pkl
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checkpoint-1000/scaler.pt
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checkpoint-1000/scheduler.bin
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checkpoint-1500/optimizer.bin
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checkpoint-1500/scaler.pt
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checkpoint-500/optimizer.bin
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prompt.txt
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persik, cat, persik 2d
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pytorch_lora_weights.safetensors
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training_params.json
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{"model": "stabilityai/sdxl-turbo", "vae_model": "", "revision": null, "tokenizer": null, "image_path": "autotrain-s8tkg-fp8ir/autotrain-data", "class_image_path": null, "prompt": "persik, cat, persik 2d", "class_prompt": null, "num_class_images": 100, "class_labels_conditioning": null, "prior_preservation": false, "prior_loss_weight": 1.0, "project_name": "autotrain-s8tkg-fp8ir", "seed": 42, "resolution": 1024, "center_crop": false, "train_text_encoder": false, "batch_size": 1, "sample_batch_size": 4, "epochs": 1, "num_steps": 2500, "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", "push_to_hub": true, "username": "adiktus9116", "validation_prompt": null, "num_validation_images": 4, "validation_epochs": 50, "checkpoints_total_limit": null, "validation_images": null, "logging": false}
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