Instructions to use CK85/Ck85 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CK85/Ck85 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CK85/Ck85", 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
metadata
license: openrail
datasets:
- HuggingFaceFV/finevideo
- fka/awesome-chatgpt-prompts
- openai/gsm8k
- Anthropic/hh-rlhf
- vivym/midjourney-prompts
- PhilipMay/stsb_multi_mt
language:
- aa
- ab
- ae
- af
- ak
- am
- an
- bi
- bm
- bn
metrics:
- accuracy
base_model:
- deepseek-ai/DeepSeek-V2.5
library_name: diffusers