Instructions to use Jinl/DiffusionNFT-baselines with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jinl/DiffusionNFT-baselines with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-3.5-medium", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Jinl/DiffusionNFT-baselines") 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 .gitattributes from Jinl/DiffusionNFT-baselines: direct link, hf CLI and curl.
- Browser
- Download file 235 Bytes
-
https://huggingface.co/Jinl/DiffusionNFT-baselines/resolve/main/.gitattributes
- Command line
-
hf download hf://Jinl/DiffusionNFT-baselines/.gitattributes
-
curl -L -o .gitattributes https://huggingface.co/Jinl/DiffusionNFT-baselines/resolve/main/.gitattributes
235 Bytes
| * text=auto | |
| *.safetensors filter=lfs diff=lfs merge=lfs -text | |
| *.pt filter=lfs diff=lfs merge=lfs -text | |
| *.wandb filter=lfs diff=lfs merge=lfs -text | |
| *.log filter=lfs diff=lfs merge=lfs -text | |
| *.tar.zst filter=lfs diff=lfs merge=lfs -text | |