---
license: apache-2.0
language:
- en
base_model:
- black-forest-labs/FLUX.1-schnell
library_name: diffusers
tags:
- realism
- finetune
- photorealism
- cinematic
extra_gated_prompt: >-
  By accessing this model, you agree to the terms of use as outlined in the
  Apache Labs Community License and confirm that you will not use the model in
  ways that violate ethical guidelines.
extra_gated_fields:
  Name: text
  Email: text
  Country: country
  Birthday: date_picker
  Affiliation: text
  Intended Use:
    type: select
    options:
    - Research
    - Education
    - Commercial
    - label: Other
      value: other
  Agreement to Apache Labs Community License: checkbox
pipeline_tag: text-to-image
---

![HEADER IMAGE](https://raw.githubusercontent.com/Aayan-Mishra/Images/refs/heads/main/APACHE%20LABS%20PRESENTS%20(3).png)

# LUMIN.1-snabb by Apache Labs

**LUMIN.1-snabb** is a high-speed diffusion model built by Apache Labs, leveraging the capabilities of **FLUX.1 schnell** to offer fast and efficient image generation without compromising detail. Optimized for rapid inference, this model is ideal for users looking to generate quality images with reduced latency.

## Model Overview

LUMIN.1-snabb is fine-tuned for quick and detailed output, maintaining a balance between visual quality and performance. With enhanced efficiency, this model is particularly suited for workflows that demand fast image generation while keeping the output quality consistent with Apache Labs’ high standards.

### Key Features
- **High-Speed Performance**: Designed for faster inference, ideal for real-time and iterative use cases.
- **Detailed Visuals**: Provides high-resolution details with a balanced color palette, suited for both creative and technical applications.
- **Optimized Efficiency**: Built on Fluxh Schnell’s framework to maximize speed without compromising on visual fidelity.

## Quickstart Guide

Here’s how to get started with **LUMIN.1-snabb** using the DiffusionPipeline:

```python
from diffusers import DiffusionPipeline

# Load the model
pipe = DiffusionPipeline.from_pretrained("apache-labs/LUMIN.1-snabb")

# Define a sample prompt
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"

# Generate an image
image = pipe(prompt).images[0]
image.show()