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 scheduler_1.bin from wsmumumu/SAMPO_VQVAE: direct link, hf CLI and curl.
- Browser
- Download file 1.01 kB
-
https://huggingface.co/wsmumumu/SAMPO_VQVAE/resolve/main/scheduler_1.bin
- Command line
-
hf download hf://wsmumumu/SAMPO_VQVAE/scheduler_1.bin
-
curl -L -o scheduler_1.bin https://huggingface.co/wsmumumu/SAMPO_VQVAE/resolve/main/scheduler_1.bin
1.01 kB
- Xet hash:
- 1e8ddd0bfe6ac8d201a80bae5bb72f07f8638834855b22c7abd25b76ce43efd5
- Size of remote file:
- 1.01 kB
- SHA256:
- 7ac2d97a6137189440051cedf897c7df46fa046a225895cf987ba750a78d52f9
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