Instructions to use callgg/voxcpm-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use callgg/voxcpm-bf16 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("callgg/voxcpm-bf16", 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
- Xet hash:
- 66c883be48100d34a0a0520caab1fc9a1d2e1b672210fdff9df0bc371d25c173
- Size of remote file:
- 1.3 GB
- SHA256:
- 62cee3da3fa803a7eb7a8fa47318ab9a6d88abe17b9d51062852f6ac86b52e3a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.