import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("Mikelue/Digdtidti")
prompt = "(firefighter suit:1.5), ultra high res, 20 years old, (male:1.4), (bodybuilder:0.7) , (Apple_Vision_Pro), <lora:Apple_Vision_Pro:0.8>,4k ,hd ,((outside a wasteland house fire)), (best quality, masterpiece:1.2), photorealistic, ((( View from oblique))), fire"
image = pipe(prompt).images[0]G
- Prompt
- (firefighter suit:1.5), ultra high res, 20 years old, (male:1.4), (bodybuilder:0.7) , (Apple_Vision_Pro), <lora:Apple_Vision_Pro:0.8>,4k ,hd ,((outside a wasteland house fire)), (best quality, masterpiece:1.2), photorealistic, ((( View from oblique))), fire
- Negative Prompt
- cartoon, lowres, bad anatomy, ((bad hands)), , text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry, artist name, young, loli, elf, 3d, illustration ,((bad-hands-5)),
Model description
BBC
Trigger words
You should use Apple_Vision_Pro to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Model tree for Mikelue/Digdtidti
Base model
runwayml/stable-diffusion-v1-5