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#diffusers

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3 items

modelsJul 23

Fast LoRA inference for Flux with Diffusers and PEFT

The Hugging Face Diffusers library now supports fast inference with LoRA adapters for Flux, enabled by the PEFT library. This integration allows for efficient model updates and low-latency inference. You can leverage this capability to deploy Flux models with improved performance. The update benefits applications requiring rapid image generation.

Key takeaways
  • Fast LoRA inference for Flux is now supported in Diffusers.
  • Enabled by PEFT library for efficient model updates.
  • Low-latency inference improves deployment performance.
HHugging Face Blog#lora#diffusers#peft#image-generation
modelsMay 21

Exploring Quantization Backends in Diffusers

The Diffusers library now supports multiple quantization backends, including bitsandbytes, dynamic, and static quantization. This allows for more flexible and efficient model deployment. You can explore different quantization methods and their trade-offs using the Diffusers library. Quantization can reduce model size and improve inference speed.

Key takeaways
  • Diffusers supports multiple quantization backends.
  • Quantization reduces model size and improves inference speed.
  • Flexible deployment options for models.
HHugging Face Blog#quantization#diffusers#model-optimization
modelsAug 22

Stable Diffusion with 🧨 Diffusers

The Stable Diffusion model is now available with Diffusers on the Hugging Face platform. This integration allows for easier model usage and customization. You can access the model through the Hugging Face interface. The Diffusers library provides a simple way to work with the model.

Key takeaways
  • Stable Diffusion integrated with Diffusers on Hugging Face.
  • Easier model usage and customization available.
  • Diffusers library simplifies model interaction.
HHugging Face Blog#stable-diffusion#diffusers#hugging-face