Instructions to use Meanblock/JEV-CPU with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Meanblock/JEV-CPU with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="Meanblock/JEV-CPU")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Meanblock/JEV-CPU", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download assets/domains/prioritization.gif from Meanblock/JEV-CPU: direct link, hf CLI and curl.
- Browser
- Download file 200 kB
-
https://huggingface.co/Meanblock/JEV-CPU/resolve/main/assets/domains/prioritization.gif
- Command line
-
hf download hf://Meanblock/JEV-CPU/assets/domains/prioritization.gif
-
curl -L -o prioritization.gif https://huggingface.co/Meanblock/JEV-CPU/resolve/main/assets/domains/prioritization.gif
200 kB

- Xet hash:
- 8bc90ca17fb609f03ee4c9ee90d4deefdeebe9fc728a3c146d01e7d7278ab5f3
- Size of remote file:
- 200 kB
- SHA256:
- 127bb39ba435cc3d5c0d34bd14b16cde5cfd67b7c710fef93a3fd546cfad89c9
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