Instructions to use wav/TemporalNet2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wav/TemporalNet2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wav/TemporalNet2", 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
Download diffusion_pytorch_model.safetensors from wav/TemporalNet2: direct link, hf CLI and curl.
- Browser
- Download file 1.45 GB
-
https://huggingface.co/wav/TemporalNet2/resolve/main/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://wav/TemporalNet2/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/wav/TemporalNet2/resolve/main/diffusion_pytorch_model.safetensors
1.45 GB
- Xet hash:
- ca3df9cf3358130e7553aeae3cea5a2505220d1ddd0963ad8a299e8a39d96aec
- Size of remote file:
- 1.45 GB
- SHA256:
- b31fdb59df59d2951354b143bb292de50c01e971aa8b83d70eb3c4e54cdcd7a2
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