Image-to-Video
Diffusers
Safetensors
English
Chinese
ImageToVideoPipeline
video generation
conversational video generation
talking human video generation
Instructions to use ssbtech/models-part1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ssbtech/models-part1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ssbtech/models-part1", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
File size: 891 Bytes
ea39373 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | {
"_class_name": "DiffusionPipeline",
"_name_or_path": "ssbtech/models-part1",
"pipeline_tag": "image-to-video",
"model_type": "image-to-video",
"framework": "pytorch",
"torch_dtype": "float16",
"requires_safetensors": true,
"components": {
"vae": "AutoencoderKL",
"unet": "UNet3DConditionModel",
"text_encoder": "CLIPTextModel",
"tokenizer": "CLIPTokenizer",
"motion_module": "MotionModule",
"scheduler": "DPMSolverMultistepScheduler"
},
"inference": {
"task": "image-to-video",
"example_inputs": {
"prompt": "A man with short gray hair plays a red electric guitar.",
"image": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png"
}
},
"base_model": "ssbtech/models-part1",
"custom_pipeline": "image_to_video",
"revision": "main"
} |