Instructions to use wfen/Cosmos3-Nano-FP8-Blockwise with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wfen/Cosmos3-Nano-FP8-Blockwise with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wfen/Cosmos3-Nano-FP8-Blockwise", 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 tokenizer.json from wfen/Cosmos3-Nano-FP8-Blockwise: direct link, hf CLI and curl.
- Browser
- Download file 7.03 MB
-
https://huggingface.co/wfen/Cosmos3-Nano-FP8-Blockwise/resolve/main/tokenizer.json
- Command line
-
hf download hf://wfen/Cosmos3-Nano-FP8-Blockwise/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/wfen/Cosmos3-Nano-FP8-Blockwise/resolve/main/tokenizer.json
7.03 MB
File too large to display, you can check the raw version instead.