Instructions to use ampp/N64_style_sd1.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ampp/N64_style_sd1.5 with Diffusers:
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("ampp/N64_style_sd1.5") prompt = "<lora:N64 Lowpoly-000001:1> n64-lowpoly style, gigachad portrait, closeup, 3d <lora:gigachadDiffusionLora_v69:0.8>" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
N64 style sd1.5

- Prompt
- <lora:N64 Lowpoly-000001:1> n64-lowpoly style, gigachad portrait, closeup, 3d <lora:gigachadDiffusionLora_v69:0.8>
- Negative Prompt
- mech, robot, easynegative, bad-hands-5
Trigger words
You should use n64-lowpoly style to trigger the image generation.
You should use low poly 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 ampp/N64_style_sd1.5
Base model
stable-diffusion-v1-5/stable-diffusion-v1-5