dolby-flux

Model trained with AI Toolkit by Ostris

Prompt

Imagine this adorable dog as the star of a cozy beachside café. Describe a sunny afternoon where it sits patiently at a table, enjoying a special dog-friendly treat while its owner sips coffee. Explore the atmosphere of the café, filled with laughter, the aroma of fresh pastries, and the sound of waves in the background, dolby_hk

Prompt

Envision this dog as an adventurous underwater explorer equipped with a tiny, high-tech diving suit. Picture it swimming alongside colorful fish and vibrant coral reefs, its eyes wide with wonder. Describe its playful interactions with friendly sea creatures and the excitement of discovering hidden treasures beneath the waves,dolby_hk

Prompt

Imagine this fluffy black dog embarking on a seaside adventure! Describe its excitement as it enjoys a boat ride, feeling the wind in its fur and the spray of the ocean. Explore its curiosity about the sights and sounds around it—seagulls flying overhead, the gentle rocking of the boat, and the vast blue horizon,dolby_hk

Trigger words

You should use dolby_hk 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('chau9ho/dolby-flux', weight_name='dolby-flux.safetensors')
image = pipeline('Imagine this adorable dog as the star of a cozy beachside café. Describe a sunny afternoon where it sits patiently at a table, enjoying a special dog-friendly treat while its owner sips coffee. Explore the atmosphere of the café, filled with laughter, the aroma of fresh pastries, and the sound of waves in the background, dolby_hk').images[0]
image.save("my_image.png")

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