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nocco_apple_v3

Model trained with AI Toolkit by Ostris

Prompt
[trigger] can on a sandy beach at sunset, surrounded by seashells and gentle ocean waves
Prompt
[trigger] can floating in space with distant stars and planets in the background, illuminated by a soft cosmic glow
Prompt
[trigger] can in a bustling urban street at night, reflecting the colorful neon signs of a busy cityscape
Prompt
[trigger] can on a picnic blanket in a lush green park, with people relaxing and trees swaying in the breeze
Prompt
[trigger] can half-buried in snow on a mountaintop, with a stunning view of the surrounding icy peaks and bright blue sky
Prompt
[trigger] can on a desert dune, surrounded by endless sand and a hot, golden sunset casting long shadows
Prompt
[trigger] can sitting on a wooden table in a cozy, candlelit cabin, with a fireplace crackling nearby
Prompt
[trigger] 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
Prompt
[trigger] can, apple taste landscape photography, sunlit setting, waterfront, architectural columns, tropical plants, Eye-level shot, straight angle, centered subject, in a hidden paradise hidden behind a waterfall, realism, (wide angle view:1.3)
Prompt
[trigger] can, apple taste, ice cold, standing in grass, outside, summer, portrait photography, Eye-level shot, centered subject, direct perspective, (front view:1.3), photo by Bruce Davidson

Trigger words

You should use n0apbc 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('Kvisten/nocco-apple-flux-v3', weight_name='nocco_apple_v3')
image = pipeline('[trigger] can on a sandy beach at sunset, surrounded by seashells and gentle ocean waves').images[0]
image.save("my_image.png")

For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers

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