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Open Source Model Profile · amy1nyc

lulu

lulu is a text-to-image LoRA from amy1nyc for FLUX.1-dev. According to the model card, it uses Amy to trigger image generation.

Publisher
amy1nyc
Task
text-to-image
Model type
Unknown
License
flux-1-dev-non-commercial-license
Library
diffusers
Publication status
Accepted · not indexed

Model overview

lulu is published by amy1nyc as a diffusers text-to-image LoRA. Hub tags list black-forest-labs/FLUX.1-dev as base model and adapter. According to the model card, it uses Amy to trigger image generation.

Recorded capabilities

FLUX.1-dev base tags

Hub tags list black-forest-labs/FLUX.1-dev as base model and adapter.

Amy trigger

According to the model card, you should use Amy to trigger image generation.

diffusers loading example

According to the model card, the publisher shows use with the diffusers AutoPipelineForText2Image workflow and lora.safetensors weights for amy1nyc/lulu.

Use cases in the source record

  • Text-to-image generation on the tagged FLUX.1-dev base using the documented Amy trigger.
  • diffusers loading experiments following the publisher AutoPipelineForText2Image and lora.safetensors example.

Limitations and unknowns

  • No evaluation results were extracted from this record.
  • No parameter count was extracted for this LoRA record.
  • License is recorded only as "other," so specific reuse terms are unknown from this record.
  • Provider state is historical snapshot data, not independently refreshed current availability.

Source and provenance

Source: amy1nyc/lulu

Captured: Unknown. Processed: 2026-09-07T19:35:18.524342+00:00.

Lulu Trained on Replicate using: https://replicate.com/ostris/flux-dev-lora-trainer/train Trigger words You should use Amy to trigger the image generation. Use it with the 🧨 diffusers library from diffusers import AutoPipelineForText2Image import torch pipeline = AutoPipelineForText2Image.from_pretrained( 'black-forest-labs/FLUX.1-dev' , torch_dtype=torch.float16).to( 'cuda' ) pipeline.load_lora_weights( 'amy1nyc/lulu' , weight_name= 'lora.safetensors' ) image = pipeline( 'your prompt' ).images[ 0 ] For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers

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