metadata
tags:
- text-to-image
- flux
- lora
- diffusers
- template:sd-lora
- ai-toolkit
widget:
- text: >-
a green aluminum can of 'NOCCO BCAA+ Apple' energy drink on a rock in a
foggy forest
output:
url: samples/1727181393674__000002500_0.jpg
- text: >-
a green aluminum can of 'NOCCO BCAA+ Apple' energy drink can in a hand of
a person
output:
url: samples/1727181430166__000002500_1.jpg
- text: >-
a green aluminum can of 'NOCCO BCAA+ Apple' can on a sandy beach at
sunset, surrounded by seashells and gentle ocean waves
output:
url: samples/1727181466660__000002500_2.jpg
- text: >-
Taylor swift holding a green aluminum can NOCCO BCAA+ Apple energy drink
can
output:
url: samples/1727181503160__000002500_3.jpg
- text: >-
'NOCCO BCAA+ Apple' can, green aluminum can dropping into crystal-clear
water, apple taste, commercial-style, the water should create dramatic
splashes and bubbles, surrounding the can in all directions, capturing
the moment of impact, high-resolution, colorful, (from above:1.2),
photo by Gregory Colbert
output:
url: samples/1727181539672__000002500_4.jpg
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: XN0APBCX
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
nocco_apple_v6
Model trained with AI Toolkit by Ostris
Trigger words
You should use XN0APBCX
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('None', weight_name='nocco_apple_v6.safetensors')
image = pipeline('a green aluminum can of 'NOCCO BCAA+ Apple' energy drink on a rock in a foggy forest').images[0]
image.save("my_image.png")
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers