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")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Meanblock/JEV-CPU", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download webgpu-demo/_headers from Meanblock/JEV-CPU: direct link, hf CLI and curl.
- Browser
- Download file 121 Bytes
-
https://huggingface.co/Meanblock/JEV-CPU/resolve/main/webgpu-demo/_headers
- Command line
-
hf download hf://Meanblock/JEV-CPU/webgpu-demo/_headers
-
curl -L -o _headers https://huggingface.co/Meanblock/JEV-CPU/resolve/main/webgpu-demo/_headers
121 Bytes
| /* | |
| Referrer-Policy: no-referrer | |
| Cross-Origin-Opener-Policy: same-origin | |
| Cross-Origin-Embedder-Policy: require-corp | |