FLUX LoRA Dostoevsky

Model Description

FLUX LoRA Dostoevsky is a fine-tuned version of the Flux text-to-image model, specifically adapted to generate images of the Russian writer Fyodor Dostoevsky. The fine-tuning process involved training on 12 photographs of Dostoevsky over 16 epochs using the Low-Rank Adaptation (LoRA) technique.

Trigger word: d0st0evsk1

Fine-Tuning Dataset

Data Source: 12 medium-quality photographs of Fyodor Dostoevsky
Number of Epochs: 16

Training Details

Training Method: Low-Rank Adaptation (LoRA)
Parameter Efficiency: LoRA introduces trainable low-rank matrices into each layer of the Transformer architecture, allowing efficient fine-tuning with a significantly reduced number of trainable parameters compared to full model fine-tuning.

Intended Use

This model is intended for generating images of Fyodor Dostoevsky based on textual descriptions. It can be used in educational materials, literary discussions, or any context where visual representations of Dostoevsky are beneficial.

Limitations and Considerations

Data Limitation: The model was trained on a limited dataset of 12 photographs, which may affect the diversity and accuracy of the generated images.
Bias and Representation: The quality and representativeness of the generated images are directly influenced by the training data. Users should be aware of potential biases resulting from the limited dataset.

Contact Information

👉 doomgrad