FLUX.1-schnell-gguf
Maintainer: city96
118
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| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
FLUX.1-schnell-gguf is a direct GGUF conversion of the FLUX.1-schnell model developed by black-forest-labs. It is a powerful image generation model capable of producing high-quality images from text descriptions. Like its predecessor, FLUX.1-schnell-gguf utilizes a rectified flow transformer architecture and was trained using latent adversarial diffusion distillation, allowing it to generate images in just 1-4 steps.
Model inputs and outputs
FLUX.1-schnell-gguf is an image-to-image model, taking in text descriptions and outputting corresponding images. The model can be used with the ComfyUI-GGUF custom node.
Inputs
- Text descriptions or prompts
Outputs
- High-quality generated images
Capabilities
FLUX.1-schnell-gguf demonstrates impressive output quality and prompt following capabilities, matching the performance of closed-source alternatives. The model can generate detailed and visually striking images from a wide range of text prompts.
What can I use it for?
FLUX.1-schnell-gguf can be a powerful tool for creative applications, such as generating custom artwork, illustrations, or concept designs. The model's speed and versatility make it suitable for use in various industries, including marketing, game development, and visual effects. Additionally, the model's Apache 2.0 license allows for personal, scientific, and commercial use.
Things to try
One interesting aspect of FLUX.1-schnell-gguf is its ability to generate images in just 1-4 steps, thanks to its latent adversarial diffusion distillation training. This makes the model particularly efficient and well-suited for real-time or interactive applications. Developers and creators are encouraged to explore the model's capabilities and integrate it into their projects using the provided resources.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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