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MA29
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t2i-lora

Text-to-Image
Diffusers
stable-diffusion
lora
Model card Files
xet
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How to use from the
Use from the
Diffusers library
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline

# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("MA29/t2i-lora")

prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]

Text-to-Image LoRA

Rank-4 LoRA for Stable Diffusion v1.5, trained for 2,000 steps at 512px on 2,163 web-harvested image-caption pairs.

Code: https://github.com/Majd1029/Text-to-Image-Generation

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