Instructions to use vidfom/Wav2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vidfom/Wav2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("vidfom/Wav2", 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
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79dc332 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | from .sd_image import SDImagePipeline
from .sd_video import SDVideoPipeline
from .sdxl_image import SDXLImagePipeline
from .sdxl_video import SDXLVideoPipeline
from .sd3_image import SD3ImagePipeline
from .hunyuan_image import HunyuanDiTImagePipeline
from .svd_video import SVDVideoPipeline
from .flux_image import FluxImagePipeline
from .cog_video import CogVideoPipeline
from .omnigen_image import OmnigenImagePipeline
from .pipeline_runner import SDVideoPipelineRunner
from .hunyuan_video import HunyuanVideoPipeline
from .step_video import StepVideoPipeline
from .wan_video import WanVideoPipeline
KolorsImagePipeline = SDXLImagePipeline
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