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
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Download README.md from Kayli/Dazai: direct link, hf CLI and curl.
- Browser
- Download file 168 Bytes
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https://huggingface.co/Kayli/Dazai/resolve/main/README.md
- Command line
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hf download hf://Kayli/Dazai/README.md
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curl -L -o README.md https://huggingface.co/Kayli/Dazai/resolve/main/README.md
168 Bytes
| license: creativeml-openrail-m | |
| datasets: | |
| - fka/awesome-chatgpt-prompts | |
| language: | |
| - en | |
| - ja | |
| metrics: | |
| - accuracy | |
| - character | |
| library_name: diffusers | |
| tags: | |
| - music | |