elg-autoshop

Model overview

elg-autoshop is published by lllahaye 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 was trained on Replicate and loads through the documented diffusers pipeline.

Recorded capabilities

Use cases in the source record

• Text-to-image generation on the tagged FLUX.1-dev base using the documented elg_autoshop trigger.
• Diffusers workflows that load lora.safetensors on FLUX.1-dev, following the model card's loading example.

Limitations and unknowns

• No evaluation results were extracted from this record.
• No parameter count was extracted for this LoRA record.
• No training hyperparameters were extracted beyond the Replicate trainer note.
• The recorded license value is only other, so reuse terms remain unclear.
• Provider state is historical snapshot data, not independently refreshed current availability.

Source and provenance

Source: lllahaye/elg-autoshop

Captured: Unknown. Processed: 2026-09-07T19:34:50.454874+00:00.

Elg Autoshop Trained on Replicate using: https://replicate.com/ostris/flux-dev-lora-trainer/train Trigger words You should use elg_autoshop 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( 'lllahaye/elg-autoshop' , 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…