LoRA text2image fine-tuning - stillerman/trdne-smol
These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were fine-tuned on the stillerman/rugs-filtered-blip dataset. You can find some example images in the following.
Training Args
{
"pretrained_model_name_or_path": "runwayml/stable-diffusion-v1-5",
"revision": null,
"dataset_name": "stillerman/rugs-filtered-blip",
"dataset_config_name": null,
"train_data_dir": null,
"image_column": "image",
"caption_column": "caption",
"validation_prompt": "peterpap.com, a red and blue rug on a white background, rug, oriental carpets, persian rug, persian carpets, symmetric indian pattern, rugs, detailed patterned rug, persian carpet, light boho carpet, an area rug, persian design, areas rugs, trending on textures. com, carpet, persian rugs, finely detailed features, hippie motifs, bohemian, highly intricate detailed",
"num_validation_images": 4,
"validation_epochs": 1,
"max_train_samples": null,
"output_dir": "model_out_dir",
"cache_dir": null,
"seed": 1337,
"resolution": 512,
"center_crop": true,
"random_flip": true,
"train_batch_size": 1,
"num_train_epochs": 8,
"max_train_steps": 250,
"gradient_accumulation_steps": 4,
"gradient_checkpointing": false,
"learning_rate": 0.0001,
"scale_lr": false,
"lr_scheduler": "cosine",
"lr_warmup_steps": 0,
"snr_gamma": null,
"use_8bit_adam": false,
"allow_tf32": false,
"dataloader_num_workers": 8,
"adam_beta1": 0.9,
"adam_beta2": 0.999,
"adam_weight_decay": 0.01,
"adam_epsilon": 1e-08,
"max_grad_norm": 1.0,
"push_to_hub": true,
"hub_token": null,
"prediction_type": null,
"hub_model_id": "trdne-smol",
"logging_dir": "logs",
"mixed_precision": null,
"report_to": "tensorboard",
"local_rank": -1,
"checkpointing_steps": 250,
"checkpoints_total_limit": null,
"resume_from_checkpoint": null,
"enable_xformers_memory_efficient_attention": false,
"noise_offset": 0,
"rank": 4,
"override_caption": null,
"append_caption": "peterpap.com, "
}
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Base model
runwayml/stable-diffusion-v1-5