Instructions to use eadx/FramePack_F1_I2V_HY_20250503 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use eadx/FramePack_F1_I2V_HY_20250503 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("eadx/FramePack_F1_I2V_HY_20250503", 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:
- b00a02611b62189d8a6f1b3fc024207cf0b88178acc77581f135f5b6028bd27c
- Size of remote file:
- 5.79 GB
- SHA256:
- cea9ec13d707f40293ce3f2a3cdeacf9ccbbe40469d2df35d95ada3780c1d766
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.