Roelof

Model overview

Roelof is published by Nikooooooo as a text-to-image LoRA. Hub tags identify diffusers, flux, and lora with black-forest-labs/FLUX.1-dev as base model and adapter. According to the model card, it was trained on Replicate and is triggered with roelof.

Recorded capabilities

Use cases in the source record

• FLUX.1-dev text-to-image work that incorporates the documented roelof trigger.
• Diffusers trials that attach lora.safetensors to the documented base model.

Limitations and unknowns

• No evaluation results were extracted from this record.
• No parameter count was extracted for this LoRA record.
• Provider state is historical snapshot data, not independently refreshed current availability.
• Training and style information comes from a brief publisher model card and has not been independently verified by Ethen.

Source and provenance

Source: Nikooooooo/Roelof

Captured: Unknown. Processed: 2026-09-07T19:34:34.786953+00:00.

Roelof --> Trained on Replicate using: https://replicate.com/ostris/flux-dev-lora-trainer/train Trigger words You should use roelof 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( 'Nikooooooo/Roelof' , 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