Instructions to use wsmumumu/SAMPO_VQVAE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wsmumumu/SAMPO_VQVAE with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wsmumumu/SAMPO_VQVAE", 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 optimizer_1.bin from wsmumumu/SAMPO_VQVAE: direct link, hf CLI and curl.
- Browser
- Download file 1.14 kB
-
https://huggingface.co/wsmumumu/SAMPO_VQVAE/resolve/main/optimizer_1.bin
- Command line
-
hf download hf://wsmumumu/SAMPO_VQVAE/optimizer_1.bin
-
curl -L -o optimizer_1.bin https://huggingface.co/wsmumumu/SAMPO_VQVAE/resolve/main/optimizer_1.bin
1.14 kB
- Xet hash:
- e04e515ccb73bd283f9804514f009d28d1efd30226030e5b3f76c541c964ea3d
- Size of remote file:
- 1.14 kB
- SHA256:
- 4da2c30c33dfcdabc5baa6220fa9fbb61b9446527188723081c8dc0830e28c93
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