metadata
tags:
- text-to-image
- flux
- lora
- diffusers
- template:sd-lora
- ai-toolkit
widget:
- text: '[trigger] woman with red hair'
output:
url: samples/1726080981710__000002000_0.jpg
- text: '[trigger] a woman holding a coffee cup, in a beanie'
output:
url: samples/1726080985911__000002000_1.jpg
- text: '[trigger] a horse is a DJ at a night club'
output:
url: samples/1726080990112__000002000_2.jpg
- text: '[trigger] a man showing off his cool new t shirt at the beach'
output:
url: samples/1726080994314__000002000_3.jpg
- text: '[trigger] a bear building a log cabin'
output:
url: samples/1726080998517__000002000_4.jpg
- text: '[trigger] woman playing the guitar, on stage, singing a song'
output:
url: samples/1726081002722__000002000_5.jpg
- text: '[trigger] hipster man with a beard'
output:
url: samples/1726081006926__000002000_6.jpg
- text: '[trigger] a man'
output:
url: samples/1726081011130__000002000_7.jpg
- text: '[trigger] a man holding a sign that says, ''this is a sign'''
output:
url: samples/1726081015337__000002000_8.jpg
- text: '[trigger] a bulldog with a shotgun, in a leather jacket with a motorcycle'
output:
url: samples/1726081019544__000002000_9.jpg
base_model: black-forest-labs/FLUX.1-schnell
instance_prompt: emojy
license: apache-2.0
flux_microsoft_emoji_lora_v1
Model trained with AI Toolkit by Ostris
Trigger words
You should use emojy
to trigger the image generation.
Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, etc.
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Use it with the 🧨 diffusers library
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-schnell', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('Zedge/Flux-Schnell-Emoji-Weights', weight_name='flux_microsoft_emoji_lora_v1')
image = pipeline('[trigger] woman with red hair').images[0]
image.save("my_image.png")
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers