Instructions to use ducnapa/Nigi3D with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ducnapa/Nigi3D with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ducnapa/Nigi3D", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from ducnapa/Nigi3D: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/ducnapa/Nigi3D/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://ducnapa/Nigi3D/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ducnapa/Nigi3D/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 918098c518ac3921e564443a1b4e828015964cf07c2047eb58d31b81e80e2051
- Size of remote file:
- 492 MB
- SHA256:
- 95572ae6a48c35e687b18c59429641abcb8a0333a65ff89b1f51f8234b73cf8c
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