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 benchmarks/data/shape777.jsonl from Meanblock/JEV-CPU: direct link, hf CLI and curl.
- Browser
- Download file 6.93 MB
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https://huggingface.co/Meanblock/JEV-CPU/resolve/main/benchmarks/data/shape777.jsonl
- Command line
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hf download hf://Meanblock/JEV-CPU/benchmarks/data/shape777.jsonl
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curl -L -o shape777.jsonl https://huggingface.co/Meanblock/JEV-CPU/resolve/main/benchmarks/data/shape777.jsonl
6.93 MB
File too large to display, you can check the raw version instead.