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Run6
Version Detail
Trained by Tensor
SDXL 1.0
2000
3
Title: Female Character LoRA - Light Blonde Bob Style Description: This LoRA model is designed to generate high-quality images of a young woman with specific physical attributes and attire, suitable for various artistic and realistic applications. Attributes: Hair Color: Light blonde Hair Style: Bob cutEye Color: BrownSkin Tone: Fair complexion with very light frecklesFacial Features: Oval face with a small nose Body Type: Slender build with a well-defined waist, gently curving hips, and a modest chest size. Clothing: Outfit: Wearing a lace-trimmed blouse, a fitted vest, and a knee-length pencil skirt. Accessories: Black choker necklace with a small pendantExpressions and Poses:Expressions: Soft and slightly enigmatic with a gentle, knowing smile. Poses: Looking away Side profile Walking forward Sitting on the ground Leaning against a tree Background and Setting: Environment: Open field under a cloudy sky. Lighting: Soft, natural lighting. Tags :Main Subject: female, light_blonde_hair, bob_cut, brown_eyes, very_light_freckles, fair_complexion, oval_face, small_nose, modest_chest, well_defined_waist, gently_curving_hips, black_choker_necklace. Actions: standing, looking_away, side_profile, walking, sitting. Background and Context: open_field, cloudy_sky, soft_natural_lighting. Style and Quality: realistic, high_resolution, detailed, serene_expression, soft_lighting. Training Details:Base Model: Stable Diffusion 1.5 (SD1.5)Training Dataset: A curated set of high-quality images tagged with the attributes, actions, and context described above. Training Parameters: Learning Rate: 1e-4Batch Size: 4Number of Epochs: 3Optimizer: AdamLoss Function: Cross-Entropy Loss implementation Steps: Data Preparation: Collect and preprocess the dataset to standardize image size and format. Tagging: Apply detailed and accurate tags to each image.Model Training: Train the model using the specified base model and parameters. Evaluation: Regularly evaluate the model’s performance using validation data to ensure it generalizes well. Fine-Tuning: Adjust the training parameters and fine-tune the model based on evaluation results. Usage: This LoRA model can be used to generate consistent and high-quality images of a young woman with the specified characteristics, suitable for use in digital art, character design, and other creative applications.
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