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4 changes: 2 additions & 2 deletions docs/source/en/tutorials/using_peft_for_inference.md
Original file line number Diff line number Diff line change
Expand Up @@ -94,7 +94,7 @@ pipeline = AutoPipelineForText2Image.from_pretrained(
pipeline.unet.load_lora_adapter(
"jbilcke-hf/sdxl-cinematic-1",
weight_name="pytorch_lora_weights.safetensors",
adapter_name="cinematic"
adapter_name="cinematic",
prefix="unet"
)
# use cnmt in the prompt to trigger the LoRA
Expand Down Expand Up @@ -688,4 +688,4 @@ Browse the [LoRA Studio](https://lorastudio.co/models) for different LoRAs to us

You can find additional LoRAs in the [FLUX LoRA the Explorer](https://huggingface.co/spaces/multimodalart/flux-lora-the-explorer) and [LoRA the Explorer](https://huggingface.co/spaces/multimodalart/LoraTheExplorer) Spaces.

Check out the [Fast LoRA inference for Flux with Diffusers and PEFT](https://huggingface.co/blog/lora-fast) blog post to learn how to optimize LoRA inference with methods like FlashAttention-3 and fp8 quantization.
Check out the [Fast LoRA inference for Flux with Diffusers and PEFT](https://huggingface.co/blog/lora-fast) blog post to learn how to optimize LoRA inference with methods like FlashAttention-3 and fp8 quantization.