metadata
tags:
- text-to-image
- flux
- lora
- diffusers
- template:sd-lora
- ai-toolkit
widget:
- text: Jacob holding a sign that says 'I am Jacob!'
output:
url: samples/1733828839445__000003000_0.jpg
- text: Jacob holding a coffee cup, in a beanie, sitting at a cafe
output:
url: samples/1733828913177__000003000_2.jpg
- text: >-
Jacob is a DJ at a night club, fish eye lens, smoke machine, lazer lights,
holding a martini
output:
url: samples/1733828950036__000003000_3.jpg
- text: >-
Jacob playing the guitar, on stage, singing a song, laser lights, punk
rocker
output:
url: samples/1733828986933__000003000_4.jpg
- text: >-
Jacob, in a post apocalyptic world, with a shotgun, in a leather jacket,
in a desert, with a motorcycle
output:
url: samples/1733829023852__000003000_5.jpg
- text: Jacob, in 90s Japanese Anime style with beautiful city background
output:
url: samples/1733829060821__000003000_6.jpg
- text: >-
Jacob is 160cm tall, wears a complete set of professional suits and walks
on the streets of Taiwan, photographed by professional photographers and
studio lighting
output:
url: images/example_huuldf0qo.png
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: Jacob
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
jacob-image-test-flux
Model trained with AI Toolkit by Ostris
Trigger words
You should use Jacob
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-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('JacobLinCool/FLUXd-jacob-v0.1', weight_name='FLUXd-jacob-v0.1.safetensors')
image = pipeline('Jacob holding a sign that says 'I am Jacob!'').images[0]
image.save("my_image.png")
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers