Added my diffusers model, 1000 steps.
Browse files- args.json +60 -0
- model_index.json +33 -0
args.json
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{
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"pretrained_model_name_or_path": "SG161222/Realistic_Vision_V2.0",
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"pretrained_vae_name_or_path": "stabilityai/sd-vae-ft-mse",
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"revision": "main",
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"tokenizer_name": null,
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"instance_data_dir": null,
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"class_data_dir": null,
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"instance_prompt": null,
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"class_prompt": null,
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"save_sample_prompt": "x_boonsie woman as amazon queen, highly saturated colors, concept art, Dan Mumford, Greg rutkowski",
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"save_sample_negative_prompt": null,
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"n_save_sample": 4,
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"save_guidance_scale": 7.5,
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"save_infer_steps": 20,
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"pad_tokens": false,
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"with_prior_preservation": true,
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"prior_loss_weight": 1.0,
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"num_class_images": 75,
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"output_dir": "/content/drive/MyDrive/stable_diffusion_weights/x_boonsie",
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"seed": 1337,
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"resolution": 512,
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"center_crop": false,
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"train_text_encoder": true,
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"train_batch_size": 1,
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"sample_batch_size": 4,
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"num_train_epochs": 14,
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"max_train_steps": 1000,
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"gradient_accumulation_steps": 1,
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"gradient_checkpointing": false,
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"learning_rate": 1e-06,
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"scale_lr": false,
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"lr_scheduler": "constant",
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"lr_warmup_steps": 0,
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"use_8bit_adam": true,
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"adam_beta1": 0.9,
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"adam_beta2": 0.999,
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"adam_weight_decay": 0.01,
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"adam_epsilon": 1e-08,
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"max_grad_norm": 1.0,
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"push_to_hub": false,
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"hub_token": null,
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"hub_model_id": null,
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"logging_dir": "logs",
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"log_interval": 10,
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"save_interval": 2000,
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"save_min_steps": 0,
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"mixed_precision": "fp16",
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"not_cache_latents": false,
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"hflip": false,
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"local_rank": -1,
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"concepts_list": [
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{
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"instance_prompt": "photo of x_boonsie woman",
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"class_prompt": "photo of a woman",
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"instance_data_dir": "/content/data/x_boonsie",
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"class_data_dir": "/content/data/woman_art-100"
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}
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],
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"read_prompts_from_txts": false
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}
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model_index.json
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{
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"_class_name": "StableDiffusionPipeline",
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"_diffusers_version": "0.15.0.dev0",
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"feature_extractor": [
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"transformers",
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"CLIPImageProcessor"
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],
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"requires_safety_checker": true,
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"safety_checker": [
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null,
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null
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],
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"scheduler": [
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"diffusers",
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"PNDMScheduler"
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],
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"text_encoder": [
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"transformers",
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"CLIPTextModel"
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],
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"tokenizer": [
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"transformers",
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"CLIPTokenizer"
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],
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"unet": [
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"diffusers",
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"UNet2DConditionModel"
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],
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"vae": [
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"diffusers",
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"AutoencoderKL"
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]
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}
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