We use essential cookies to make our site work. With your consent, we may also use non-essential cookies to improve user experience and analyze website traffic…

GLM-5.1 - state-of-the-art agentic engineering, now available on DeepInfra!

How to use CivitAI LoRAs: 5-Minute AI Guide to Stunning Double Exposure Art
Published on 2025.01.23 by Oguz Vuruskaner
How to use CivitAI LoRAs: 5-Minute AI Guide to Stunning Double Exposure Art

Double exposure is a photography technique that combines multiple images into a single frame, creating a dreamlike and artistic effect. With the advent of AI image generation, we can now create stunning double exposure art in minutes using LoRA models. In this guide, we'll walk through how to use the Flux Double Exposure Magic LoRA from CivitAI with DeepInfra's deployment platform.

What You'll Need

  • A CivitAI account (free)
  • A DeepInfra account (free)

Set Up a LoRA model

  1. Log in to your DeepInfra account
  2. Navigate to the Deployments section
  3. Click the "New Deployment" button in the top right corner
  4. Select "LoRA text to image" from the options

Once you navigate to this section, you will see a screen like this: Text-to-image LoRA Dashboard 5. Write your preferred model name. 6. We'll use FLUX Dev for this LoRA. You can keep it as it is. 7. Add the following CivitAI URL: https://civitai.com/models/715497/flux-double-exposure-magic?modelVersionId=859666 8. Click "Upload" button, and that's it. VOILA!

Once LoRA processing has completed, you should navigate to

 http://deepinfra.com/<your_name>/<lora_name>
copy

When you have navigated, you should view our classical dashboard, but with your LoRA name.

An Example: Cyberpunk Double Exposure

Now let's create some stunning visuals... Let's break down this stunning example:

bo-exposure, double exposure, cyberpunk city, robot face
copy

Example of AI-generated cyberpunk double exposure art

Key Takeaway ⚠️

Notice how we use BOTH bo-exposure and double exposure. This combination is crucial - using both terms together gives you the best double exposure effect.

More tutorials are on the way. See you in the next one 👋

Related articles
Kimi K2.5 API Benchmarks: Latency, Throughput & CostKimi K2.5 API Benchmarks: Latency, Throughput & Cost<p>About Kimi K2.5 Kimi K2.5 is Moonshot AI&#8217;s flagship open-source reasoning model, released in January 2026. It is a native multimodal agentic model built through continual pretraining on approximately 15 trillion mixed visual and text tokens. The model features a Mixture-of-Experts (MoE) architecture with 1 trillion total parameters and 32 billion activated parameters. Kimi K2.5 [&hellip;]</p>
Qwen3.5 0.8B API Benchmarks: Latency, Throughput & CostQwen3.5 0.8B API Benchmarks: Latency, Throughput & Cost<p>About Qwen3.5 0.8B (Reasoning) Qwen3.5 0.8B is part of Alibaba Cloud&#8217;s Qwen3.5 Small Model Series, released on March 2, 2026. Designed under the philosophy of &#8220;More Intelligence, Less Compute,&#8221; it targets edge devices, mobile phones, and low-latency applications where battery life and memory constraints are critical. It employs an Efficient Hybrid Architecture combining Gated Delta [&hellip;]</p>
Use OpenAI API clients with LLaMasUse OpenAI API clients with LLaMasGetting started # create a virtual environment python3 -m venv .venv # activate environment in current shell . .venv/bin/activate # install openai python client pip install openai Choose a model meta-llama/Llama-2-70b-chat-hf [meta-llama/L...