metadata
base_model: black-forest-labs/FLUX.1-schnell
license: apache-2.0
tags:
- autotrain
- spacerunner
- text-to-image
- flux
- lora
- diffusers
- template:sd-lora
widget:
- text: >-
A realistic IPhone 15 selfie of 5 years old female FluxTManu. Ultra
realistic. Background blur.
output:
url: samples/1726184803539__000001000_0.jpg
- text: >-
A cinematic shot of 1 year old female FluxTManu surfing a big wave in
Thailand. Ultra realistic. Background blur
output:
url: samples/1726184808712__000001000_1.jpg
- text: >-
A photo of 1 year old female FluxTManu working in front of a computer in a
tech company in Silicon Valley. Background blur.
output:
url: samples/1726184813888__000001000_2.jpg
instance_prompt: FluxTManu
fmanux-treinado
Model trained with AI Toolkit by Ostris
- Prompt
- A realistic IPhone 15 selfie of 5 years old female FluxTManu. Ultra realistic. Background blur.
- Prompt
- A cinematic shot of 1 year old female FluxTManu surfing a big wave in Thailand. Ultra realistic. Background blur
- Prompt
- A photo of 1 year old female FluxTManu working in front of a computer in a tech company in Silicon Valley. Background blur.
Trigger words
You should use FluxTManu 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('RodrigoFlorencio/fmanux-treinado', weight_name='fmanux-treinado')
image = pipeline('A realistic IPhone 15 selfie of 5 years old female FluxTManu. Ultra realistic. Background blur.').images[0]
image.save("my_image.png")
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers