metadata
license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
language:
- en
tags:
- flux
- diffusers
- lora
- replicate
base_model: black-forest-labs/FLUX.1-dev
pipeline_tag: text-to-image
instance_prompt: animexl
widget:
- text: >-
animexl a majestic celestial dragon flying through a star-filled sky, its
scales shimmering with a mix of gold and silver, glowing runes etched
along its body, surrounded by glowing nebula clouds and twinkling stars, a
sense of vastness and divinity, hyper-detailed scales and cosmic
background
output:
url: images/example_f5qbha2v5.png
- text: >-
animexl an ethereal elf princess with glowing silver hair, wearing a
flowing emerald gown adorned with golden patterns, sitting by a glowing
blue lake in an enchanted forest, surrounded by bioluminescent flowers,
glowing fireflies, and ancient stone ruins covered in moss, soft moonlight
shining through the mist, ultra-detailed face and clothing texture
output:
url: images/example_377tmyn08.png
- text: >-
animexl a lone wanderer in a torn black cloak, standing in a desolate
wasteland with crumbling skyscrapers in the distance, carrying a glowing
energy sword, the sky filled with ominous red clouds, lightning striking
in the distance, detailed cracks in the dry ground, atmospheric
perspective with dusty air and a sense of mystery"
output:
url: images/example_1fnaylit5.png
Animexl
Trained on Replicate using:
https://replicate.com/ostris/flux-dev-lora-trainer/train
Trigger words
You should use animexl
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('Nishit2411/AnimeXL', 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