Instructions to use MercuryNex/hyperlcm-openvino with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MercuryNex/hyperlcm-openvino with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MercuryNex/hyperlcm-openvino", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Download vae_decoder/openvino_model.bin from MercuryNex/hyperlcm-openvino: direct link, hf CLI and curl.
- Browser
- Download file 196 MB
-
https://huggingface.co/MercuryNex/hyperlcm-openvino/resolve/main/vae_decoder/openvino_model.bin
- Command line
-
hf download hf://MercuryNex/hyperlcm-openvino/vae_decoder/openvino_model.bin
-
curl -L -o openvino_model.bin https://huggingface.co/MercuryNex/hyperlcm-openvino/resolve/main/vae_decoder/openvino_model.bin
196 MB
- Xet hash:
- 172cd9404973a86b11326e32cf548f510b8d8e85ea55a2a182c1ccdd0e93c5db
- Size of remote file:
- 196 MB
- SHA256:
- 06afca9d0ba50f9d36b9f25ac99cd286e02a8862f17da1845a2f17254f253805
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