Instructions to use taraxis/nekotest1-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use taraxis/nekotest1-1 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-2-1-base", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("taraxis/nekotest1-1") prompt = "nekotst" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download pytorch_lora_weights.bin from taraxis/nekotest1-1: direct link, hf CLI and curl.
- Browser
- Download file 3.42 MB
-
https://huggingface.co/taraxis/nekotest1-1/resolve/main/pytorch_lora_weights.bin
- Command line
-
hf download hf://taraxis/nekotest1-1/pytorch_lora_weights.bin
-
curl -L -o pytorch_lora_weights.bin https://huggingface.co/taraxis/nekotest1-1/resolve/main/pytorch_lora_weights.bin
3.42 MB
- Xet hash:
- f95702db4832652f258a7bea13a60d710f1eebf6579c9574c7cee70de3e9fee8
- Size of remote file:
- 3.42 MB
- SHA256:
- b9cb4a0d903d960657855ec3283877bdfd808a375bb12d08d247b828257f1215
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.