Instructions to use WyzerLearningInc/CatInSpace with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Inference
- Notebooks
- Google Colab
- Kaggle
Upload 12 files
Browse files- dataset_config.toml +17 -0
- lingospace-01.safetensors +3 -0
- lingospace-02.safetensors +3 -0
- lingospace-03.safetensors +3 -0
- lingospace-04.safetensors +3 -0
- lingospace-05.safetensors +3 -0
- lingospace-06.safetensors +3 -0
- lingospace-07.safetensors +3 -0
- lingospace-08.safetensors +3 -0
- lingospace-09.safetensors +3 -0
- lingospace-10.safetensors +3 -0
- training_config.toml +55 -0
dataset_config.toml
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[[datasets]]
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[[datasets.subsets]]
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num_repeats = 2
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image_dir = "/content/drive/MyDrive/Loras/lingospace/dataset"
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[general]
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resolution = 1024
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shuffle_caption = true
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keep_tokens = 1
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flip_aug = false
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caption_extension = ".txt"
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enable_bucket = true
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bucket_no_upscale = false
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bucket_reso_steps = 64
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min_bucket_reso = 256
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max_bucket_reso = 4096
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lingospace-01.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:1baf7504648f806a42bd23fd1a3d19be9951cb9d6274d0c884cd99f999795dd6
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size 50954508
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lingospace-02.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:1b1dc5ecb6db37ac2a6990e28d85636a6e4ce940380b9ad2b558d64a46a58424
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lingospace-03.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:df35df3b028b2150762dd0f07ef7418dd871510e47904737fa0bd408d131baa5
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size 50954508
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lingospace-04.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:79094cc2bfe6aa7bacc71e9f88fbe8b69e160a9d3df91cfd9e604d2576ba2602
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size 50954508
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lingospace-05.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:071c8b851d04ed6a1c5dff5dc3ddc3d6cd191c9ef536150cefbcb081c9d84278
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lingospace-06.safetensors
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oid sha256:099911f1db72b2f5d524f02b29e96dfe593418d2bbaeb41b207660cc7bc7217e
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lingospace-07.safetensors
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oid sha256:92bb8c835203c6557fc9efc6ed8b626c4691703eff5b97949a77b32a5bf1b3c5
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lingospace-08.safetensors
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oid sha256:4b4afa572fe4a47722126c36e4c993ba7cc6a124a3d80047162f5056adb5581d
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lingospace-09.safetensors
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oid sha256:8dfad8c13333ffff81ca7dd4bc774020bdbd7d2545f0990ee8c30ba747bbdc15
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lingospace-10.safetensors
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oid sha256:93579a0c065ac6f9940be39ce5379894883bf8ca502f65e036b877804fc6e120
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training_config.toml
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[network_arguments]
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unet_lr = 0.0003
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text_encoder_lr = 6e-5
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network_dim = 8
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network_alpha = 4
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network_module = "networks.lora"
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network_train_unet_only = false
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[optimizer_arguments]
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learning_rate = 0.0003
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lr_scheduler = "cosine_with_restarts"
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lr_scheduler_num_cycles = 3
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lr_warmup_steps = 8
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optimizer_type = "AdamW8bit"
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optimizer_args = [ "weight_decay=0.1", "betas=[0.9,0.99]",]
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loss_type = "l2"
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max_grad_norm = 1.0
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[training_arguments]
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lowram = true
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pretrained_model_name_or_path = "/content/sd_xl_base_1.0.safetensors"
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vae = "/content/sdxl_vae.safetensors"
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max_train_epochs = 10
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train_batch_size = 6
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seed = 42
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max_token_length = 225
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xformers = false
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sdpa = true
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min_snr_gamma = 8.0
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no_half_vae = true
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gradient_checkpointing = true
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gradient_accumulation_steps = 1
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max_data_loader_n_workers = 1
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persistent_data_loader_workers = true
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mixed_precision = "fp16"
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full_fp16 = true
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full_bf16 = false
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cache_latents = true
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cache_latents_to_disk = true
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cache_text_encoder_outputs = false
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min_timestep = 0
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max_timestep = 1000
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prior_loss_weight = 1.0
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multires_noise_iterations = 6
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multires_noise_discount = 0.3
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[saving_arguments]
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save_precision = "fp16"
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save_model_as = "safetensors"
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save_every_n_epochs = 1
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save_last_n_epochs = 10
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output_name = "lingospace"
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output_dir = "/content/drive/MyDrive/Loras/lingospace/output"
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log_prefix = "lingospace"
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logging_dir = "/content/drive/MyDrive/Loras/_logs"
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