Instructions to use ali-vilab/MS-Image2Video with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- OpenCLIP
How to use ali-vilab/MS-Image2Video with OpenCLIP:
import open_clip model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms('hf-hub:ali-vilab/MS-Image2Video') tokenizer = open_clip.get_tokenizer('hf-hub:ali-vilab/MS-Image2Video') - Notebooks
- Google Colab
- Kaggle
File size: 609 Bytes
94867b2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"framework": "pytorch",
"task": "image-to-video",
"model": {
"type": "image-to-video-model",
"model_args": {
"ckpt_clip": "open_clip_pytorch_model.bin",
"ckpt_unet": "base_03_alldata_fps_v_80g_0789000.pth",
"ckpt_autoencoder": "v2-1_512-ema-pruned.ckpt",
"seed": 666
},
"model_cfg": {
"batch_size": 1,
"target_fps": 8,
"max_frames": 32,
"latent_hei": 32,
"latent_wid": 56
}
},
"pipeline": {
"type": "image-to-video-task-pipeline"
}
}
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