Instructions to use Kayli/Dazai with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Kayli/Dazai with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Kayli/Dazai", 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
|
Download README.md from Kayli/Dazai: direct link, hf CLI and curl.
- Browser
- Download file 168 Bytes
-
https://huggingface.co/Kayli/Dazai/resolve/main/README.md
- Command line
-
hf download hf://Kayli/Dazai/README.md
-
curl -L -o README.md https://huggingface.co/Kayli/Dazai/resolve/main/README.md
168 Bytes
metadata
license: creativeml-openrail-m
datasets:
- fka/awesome-chatgpt-prompts
language:
- en
- ja
metrics:
- accuracy
- character
library_name: diffusers
tags:
- music