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Hybrid Inference
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You are viewing v0.33.1 version. A newer version v0.38.0 is available.
Hybrid Inference
Empowering local AI builders with Hybrid Inference
Hybrid Inference is an experimental feature. Feedback can be provided here.
Why use Hybrid Inference?
Hybrid Inference offers a fast and simple way to offload local generation requirements.
- 🚀 Reduced Requirements: Access powerful models without expensive hardware.
- 💎 Without Compromise: Achieve the highest quality without sacrificing performance.
- 💰 Cost Effective: It’s free! 🤑
- 🎯 Diverse Use Cases: Fully compatible with Diffusers 🧨 and the wider community.
- 🔧 Developer-Friendly: Simple requests, fast responses.
Available Models
- VAE Decode 🖼️: Quickly decode latent representations into high-quality images without compromising performance or workflow speed.
- VAE Encode 🔢: Efficiently encode images into latent representations for generation and training.
- Text Encoders 📃 (coming soon): Compute text embeddings for your prompts quickly and accurately, ensuring a smooth and high-quality workflow.
Integrations
- SD.Next: All-in-one UI with direct supports Hybrid Inference.
- ComfyUI-HFRemoteVae: ComfyUI node for Hybrid Inference.
Changelog
- March 10 2025: Added VAE encode
- March 2 2025: Initial release with VAE decoding
Contents
The documentation is organized into three sections:
- VAE Decode Learn the basics of how to use VAE Decode with Hybrid Inference.
- VAE Encode Learn the basics of how to use VAE Encode with Hybrid Inference.
- API Reference Dive into task-specific settings and parameters.