GAG - RPG Potions | LoRa XL版本v 0.1 (ID: 26975)

GAG = Game Asset Generator
? Date: 2023-10-23T12:19:42

FF_Potion_Generator ?⚗️✨

• Resolution: 1024x1024

• Architecture: stable-diffusion-xl-v1-base/lora

• Network Dim/Rank: 32.0

• Alpha: 1.0

• Module: networks.lora

• Learning Rates:

  • Overall: 0.0005

  • UNet: 0.0005

  • Text Encoder: 5e-05

• Optimizer: bitsandbytes.optim.adamw.AdamW8bit(weight_decay=0.1)

• Scheduler: cosine_with_restarts

• Warmup steps: 0

• Training Details:

  • Epoch: 15

  • Batches per epoch: 250

  • Gradient accumulation steps: 1

• Images:

  • Train images: 1000

  • Regularization images: 0

• Noise & Regularization:

  • Multires noise iterations: 6.0

  • Multires noise discount: 0.3

  • Min SNR gamma: 5.0

  • Zero terminal SNR: True

  • Max grad norm: 1.0

  • Clip skip: 1

• Dataset: 1 Directory with 500 images

• UNet Weights:

  • Average magnitude: 2.9637

  • Average strength: 0.0109

• Text Encoder Weights:

  • (1) Magnitude: 1.7253 | Strength: 0.0086

  • (2) Magnitude: 1.7251 | Strength: 0.0067

? Tags:

potion, painting of one health potion, potion of healing, health potion, magic potions, magical potions, alchemy concept, hyper realistic poison bottle, rendered art, making a potion, potions, fantasy game spell symbol, rpg game item, alchemist bottles, rpg item render, stylized game art, game icon stylized, hyperdetailed scp artifact jar, 3 d icon for mobile game, 3 d render stylized, casting a spell on a potion ... and 904 more!

Starting my GAG Serries ? ?

This one is a Potion LORA for 2.1 SD models.

Depending on the model you will get quite different results.

You can use a background remover while generating and get:

again this is a test LORA and is heavily dependent on the input model.

LyCORIS version will be up for testing in a few hours.
And a 2.1 Model is expected in 48-60 hours

For PIXALISATION try:
PIXHELL by R6SPY ?

PS: so far you can use it for demonstration purposes (preview version)

with version 1.0 above (lora and models of GAG series)
two versions will be available:
Licensed - can be licensed for in-game usage upon request (using only my work and licensed images from my end)
Community - using sourced free images and sources but you are responsible is used commercially in your project ¯\_(ツ)_/¯ ? ?

描述:

Training data:
ss_batch_size_per_device: "10",

ss_bucket_info: "{"buckets": {"0": {"resolution": [384, 576], "count": 2440}, "1": {"resolution": [512, 512], "count": 49520}, "2": {"resolution": [576, 384], "count": 1720}}, "mean_img_ar_error": 0.0}",

ss_bucket_no_upscale: "True",

ss_cache_latents: "True",

ss_caption_dropout_every_n_epochs: "0",

ss_caption_dropout_rate: "0.0",

ss_caption_tag_dropout_rate: "0.0",

ss_clip_skip: "None",

ss_color_aug: "False",

ss_enable_bucket: "True",

ss_epoch: "2",

ss_face_crop_aug_range: "None",

ss_flip_aug: "False",

ss_full_fp16: "False",

ss_gradient_accumulation_steps: "1",

ss_gradient_checkpointing: "False",

ss_keep_tokens: "0",

ss_learning_rate: "0.0001",

ss_lowram: "False",

ss_lr_scheduler: "linear",

ss_lr_warmup_steps: "1074",

ss_max_bucket_reso: "1024",

ss_max_grad_norm: "1.0",

ss_max_token_length: "225",

ss_max_train_steps: "10736",

ss_min_bucket_reso: "256",

ss_mixed_precision: "fp16",

ss_network_alpha: "1.0",

ss_network_args: "{"conv_dim": "1", "conv_alpha": "1"}",

ss_network_dim: "16",

ss_network_module: "networks.lora",

ss_noise_offset: "0.1",

ss_num_batches_per_epoch: "5368",

ss_num_epochs: "2",

ss_num_reg_images: "0",

ss_num_train_images: "53680",

ss_optimizer: "lion_pytorch.lion_pytorch.Lion",

ss_output_name: "idle.Potionsv_qv",

ss_prior_loss_weight: "1.0",

ss_random_crop: "False",

ss_reg_dataset_dirs: "{}",

ss_resolution: "(512, 512)",

ss_sd_model_name: "stabilityai/stable-diffusion-2-1",

ss_sd_scripts_commit_hash: "00f74d271ab015916a75d6cee6f3af9b0b89f764",

ss_seed: "None",

ss_session_id: "3030622464",

ss_shuffle_caption: "True",

ss_text_encoder_lr: "5e-05",

ss_total_batch_size: "10",

ss_training_comment: "None",

ss_training_finished_at: "1679317172.8840992",

ss_training_started_at: "1679302821.9685614",

ss_unet_lr: "0.0001",

ss_v2: "True"

训练词语: