flux lora korea palace

Introduction

FLUX-LORA-KOREA-PALACE is a text-to-image model designed to generate images using specific prompts. It is part of the Hugging Face ecosystem and utilizes the LoRA (Low-Rank Adaptation) technique to enhance text-to-image generation capabilities.

Architecture

The model builds upon the base model FLUX.1-dev from Black Forest Labs. It employs the LoRA technique to fine-tune image generation while maintaining efficient resource usage. The model supports the diffusers library, which facilitates the diffusion process in image generation.

Training

The model is trained to generate images based on specific text prompts, such as "Gyeongbokgung Palace in Seoul, South Korea." It uses trigger words like "korea palace" to initiate the generation process. The training process involves adapting the base model using LoRA weights to specialize in generating images of Korean palaces.

Guide: Running Locally

To run the model locally, follow these steps:

1. Download the Model Weights: Access the Files & Versions tab on the Hugging Face model page to download the weights in Safetensors format.
2. Install Dependencies: Ensure you have Python installed, along with the diffusers library and torch.

   pip install diffusers torch
   

3. Load the Model: Use the following Python code to load the model and generate an image:

   from diffusers import AutoPipelineForText2Image
   import torch
   
   pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to('cuda')
   pipeline.load_lora_weights('openfree/flux-lora-korea-palace', weight_name='flux-lora-korea-palace.safetensors')
   image = pipeline('Gyeongbokgung Palace in Seoul, South Korea. It is a large building with stairs leading up to the entrance, surrounded by a wall. In the background, there are other buildings, mountains, and a clear blue sky. [trigger]').images[0]
   image.save("my_image.png")
   

4. Suggested Hardware: Use a cloud GPU (such as those from AWS, GCP, or Azure) for optimal performance when running the model, especially for large image generation tasks.

License

The model is released under the flux-1-dev-non-commercial-license. This license allows for non-commercial use only. For detailed terms, refer to the license document.