antique_table_b2_5e5_lora32_cdr0_s3000

Model overview

antique_table_b2_5e5_lora32_cdr0_s3000 is published by TheNetherWatcher as a 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 the TOK trigger and was trained with the linked Replicate LoRA trainer.

Recorded capabilities

Use cases in the source record

• Text-to-image generation with FLUX.1-dev workflows that include the documented TOK trigger.
• Diffusers experiments that load lora.safetensors onto the FLUX.1-dev pipeline.

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 output details come from a brief publisher model card and have not been independently verified by Ethen.

Source and provenance

Source: TheNetherWatcher/antique_table_b2_5e5_lora32_cdr0_s3000

Captured: Unknown. Processed: 2026-09-07T19:34:37.659038+00:00.

Antique_Table_B2_5E5_Lora32_Cdr0_S3000 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( 'TheNetherWatcher/antique_table_b2_5e5_lora32_cdr0_s3000' , weight_name= 'lora.safetensors' ) image = pipeline( 'your prompt' ).images[ 0 ] For more details, including weighting, merging and fusing…