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-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/stable-diffusion-xl-base-1.0
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instance_prompt: julieta chaves
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license: openrail++
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---
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# AutoTrain SDXL LoRA DreamBooth - VictorGrinch/JulietaChaves
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<Gallery />
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## Model description
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These are VictorGrinch/JulietaChaves LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
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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 julieta chaves 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](VictorGrinch/JulietaChaves/tree/main) them in the Files & versions tab.
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checkpoint-1000/optimizer.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:eb740a493b9dde9d0669f0bd2daa84530e71ba43df76668b33a86cd7a543b5e9
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size 47392882
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checkpoint-1000/pytorch_lora_weights.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:2e7b91471d2ba77bacad772440c1a2440a0f0626562b28528cf9d856032dc419
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checkpoint-1000/random_states_0.pkl
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size 14408
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checkpoint-1000/scaler.pt
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size 988
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checkpoint-1000/scheduler.bin
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size 1000
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checkpoint-500/optimizer.bin
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oid sha256:d144184ea94fb79233ee9899989ae8c06a78fb776c9d1390adc3acd9eac0e99f
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size 47392882
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checkpoint-500/pytorch_lora_weights.safetensors
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oid sha256:32043475f744de12cd63ca39232f3a5bf32aac23b4c6e28969bc15d0985bb65b
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size 23390424
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checkpoint-500/random_states_0.pkl
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oid sha256:8ffebba341af3b052f64013fb9c07cae77b186b1623e73d33a2085ec149d24d9
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checkpoint-500/scaler.pt
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oid sha256:18b984273ea2d45b7ffb1d047bb359d93111e41fcad70d16a1b453fd38f72636
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size 988
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checkpoint-500/scheduler.bin
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oid sha256:6cf34ac8dd2addc454aeb1ee4eaba3267c2841857e117be40ac2ed02cf581c9c
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size 1000
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prompt.txt
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julieta chaves
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pytorch_lora_weights.safetensors
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oid sha256:2e7b91471d2ba77bacad772440c1a2440a0f0626562b28528cf9d856032dc419
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size 23390424
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pytorch_lora_weights_kohya.safetensors
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training_params.json
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{"model": "stabilityai/stable-diffusion-xl-base-1.0", "vae_model": "", "revision": null, "tokenizer": null, "image_path": "JulietaChaves/autotrain-data", "class_image_path": null, "prompt": "julieta chaves", "class_prompt": null, "num_class_images": 100, "class_labels_conditioning": null, "prior_preservation": false, "prior_loss_weight": 1.0, "project_name": "JulietaChaves", "seed": 42, "resolution": 1024, "center_crop": false, "train_text_encoder": false, "batch_size": 1, "sample_batch_size": 4, "epochs": 1, "num_steps": 1000, "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": "VictorGrinch", "validation_prompt": null, "num_validation_images": 4, "validation_epochs": 50, "checkpoints_total_limit": null, "validation_images": null, "logging": false}
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