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Open Source Model Profile · asherapple2

asher-hot

asher-hot is a text-to-image LoRA from asherapple2. Its model card documents the ASHERHOT trigger and Replicate-based training for FLUX.1-dev workflows.

Publisher
asherapple2
Task
text-to-image
Model type
Unknown
License
flux-1-dev-non-commercial-license
Library
diffusers
Publication status
Accepted · not indexed

Model overview

asher-hot is published by asherapple2 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 was trained on Replicate and uses ASHERHOT as the trigger word.

Recorded capabilities

ASHERHOT trigger

The model card says to use ASHERHOT to trigger image generation.

FLUX.1-dev base tags

Hub tags list black-forest-labs/FLUX.1-dev as base model and adapter, matching the card's loading snippet.

Diffusers loading snippet

The model card documents diffusers AutoPipelineForText2Image usage with lora.safetensors.

Use cases in the source record

  • Subject-style text-to-image generation with FLUX.1-dev workflows that include the documented ASHERHOT trigger.
  • Diffusers experiments that load lora.safetensors over 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 subject details come from a brief publisher model card and have not been independently verified by Ethen.

Source and provenance

Source: asherapple2/asher-hot

Captured: Unknown. Processed: 2026-09-07T19:34:40.268978+00:00.

Asher Hot --> Trained on Replicate using: https://replicate.com/ostris/flux-dev-lora-trainer/train Trigger words You should use ASHERHOT 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( 'asherapple2/asher-hot' , 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 di…

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