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A realism LoRA for **Krea 2**. It pushes Krea 2 toward natural, candid, true-to-life photography — everyday people, places, and light — without needing any "photorealistic / 8k / DSLR" style keywords. Just write a normal, descriptive sentence and let the LoRA do the rest. Trained with the FAL Krea LoRA Trainer on `krea/Krea-2-Raw` and meant to be used directly on `krea/Krea-2-Turbo` (per Krea's recommended workflow of training on Raw and running on Turbo). **No trigger word is required.** Simply describe the scene in plain natural language. Longer, descriptive single-sentence prompts work best, e.g.:

Image generation
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This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the glue dataset. It achieves the following results on the evaluation set: - Loss: 0.4422 - Accuracy: 0.8372 The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 33 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 50 - mixed_precision_training: Native AMP

Text analysis
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Text generation
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eng_latn_100mb

goldfish-models

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Text generation
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fra_latn_1000mb

goldfish-models

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Text generation
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ita_latn_1000mb

goldfish-models

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Text generation
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rus_cyrl_1000mb

goldfish-models

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Text generation
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srp_cyrl_1000mb

goldfish-models

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Text generation
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Begonya-1.5B

goncimik

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