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Open Source Model Profile · TypoDZN

antonio2

antonio2 is a text-to-image LoRA from TypoDZN for FLUX.1-dev. According to the model card, it uses antonio2 to trigger image generation.

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

Model overview

antonio2 is published by TypoDZN 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 antonio2 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.

antonio2 trigger

According to the model card, you should use antonio2 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 TypoDZN/antonio2.

Use cases in the source record

  • Text-to-image generation on the tagged FLUX.1-dev base using the documented antonio2 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: TypoDZN/antonio2

Captured: Unknown. Processed: 2026-09-07T19:35:16.819226+00:00.

Antonio2 Trained on Replicate using: https://replicate.com/ostris/flux-dev-lora-trainer/train Trigger words You should use antonio2 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( 'TypoDZN/antonio2' , 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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