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Open Source Model Profile · Muapi

fluxgiant

fluxgiant is a text-to-image LoRA from Muapi for Flux.1 D. According to the model card, its trained word is giant.

Publisher
Muapi
Task
text-to-image
Model type
Unknown
License
openrail++
Library
diffusers
Publication status
Accepted · not indexed

Model overview

fluxgiant is published by Muapi 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, the base is Flux.1 D and the trained word is giant.

Recorded capabilities

FLUX.1-dev base tags

Hub tags list black-forest-labs/FLUX.1-dev as base model and adapter, and the publisher names Flux.1 D as base model.

Giant trained word

According to the model card, the trained word is giant.

MUAPI usage example

According to the model card, the publisher shows a MUAPI flux_dev_lora_image request with 1024 by 1024 sizing.

Use cases in the source record

  • Text-to-image generation on the tagged FLUX.1-dev base using the documented giant word.
  • MUAPI API experiments following the publisher flux_dev_lora_image request example.

Limitations and unknowns

  • No evaluation results were extracted from this record.
  • No parameter count was extracted for this LoRA record.
  • No detailed training hyperparameters were extracted beyond the base and trained-word note.
  • Provider state is historical snapshot data, not independently refreshed current availability.

Source and provenance

Source: Muapi/fluxgiant

Captured: Unknown. Processed: 2026-09-07T19:36:05.540833+00:00.

FluxGiant Base model : Flux.1 D Trained words : giant 🧠 Usage (Python) 🔑 Get your MUAPI key from muapi.ai/access-keys import requests, os url = "https://api.muapi.ai/api/v1/flux_dev_lora_image" headers = { "Content-Type" : "application/json" , "x-api-key" : os.getenv( "MUAPIAPP_API_KEY" )} payload = { "prompt" : "masterpiece, best quality, 1girl, looking at viewer" , "model_id" : [{ "model" : "civitai:700672@783979" , "weight" : 1.0 }], "width" : 1024 , "height" : 1024 , "num_images" : 1 } print (requests.post(url, headers=headers, json=payload).json())

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