flux lora car rolls royce

Introduction

The FLUX-LORA-CAR-ROLLS-ROYCE model is a text-to-image model designed to generate images of Rolls Royce cars using specific prompts. It is built using the FLUX framework and trained with AutoTrain, utilizing various model templates and libraries like diffusers and LORA.

Architecture

This model uses the base model from black-forest-labs/FLUX.1-dev. It integrates various tags such as autotrain, spacerunner, text-to-image, flux, lora, and diffusers. This combination allows for generating detailed images based on textual descriptions.

Training

The model was trained using AutoTrain, enabling efficient fine-tuning and adaptation to specific tasks. It uses LoRA (Low-Rank Adaptation) to enhance its capabilities in generating images based on detailed prompts.

Guide: Running Locally

1. Install Dependencies: Ensure you have Python installed along with necessary libraries such as torch and diffusers.
2. Clone the Repository: Download the model files from the Files & versions tab.
3. Load Weights: Use the diffusers library to load the model and its LoRA weights.

   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('seawolf2357/flux-lora-car-rolls-royce', weight_name='flux-lora-car-rolls-royce')
   image = pipeline('A person in a bustling cafe car rollsroyce').images[0]
   image.save("my_image.png")
   

4. Run Inference: Generate images by providing specific prompts to the pipeline.

For enhanced performance, using cloud GPUs such as those from AWS, Google Cloud, or Azure is recommended to handle the model's computational requirements.

License

The model is released under the flux-1-dev-non-commercial-license. The full license details are available at this link. This license allows for non-commercial use, with restrictions on commercial applications.