issam

Model overview

issam is published by zakariamtl 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 uses TOK as the trigger.

Recorded capabilities

Use cases in the source record

• Text-to-image generation on the tagged FLUX.1-dev base using the documented TOK trigger.
• Diffusers loading experiments following the publisher AutoPipelineForText2Image 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: zakariamtl/issam

Captured: Unknown. Processed: 2026-09-07T19:35:33.155061+00:00.

Issam Trained on Replicate using: https://replicate.com/ostris/flux-dev-lora-trainer/train Trigger words You should use TOK 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( 'zakariamtl/issam' , 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