Instructions to use thhaus/nemotron4-tokenizer2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thhaus/nemotron4-tokenizer2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("thhaus/nemotron4-tokenizer2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from thhaus/nemotron4-tokenizer2: direct link, hf CLI and curl.
- Browser
- Download file 18.1 MB
-
https://huggingface.co/thhaus/nemotron4-tokenizer2/resolve/main/tokenizer.json
- Command line
-
hf download hf://thhaus/nemotron4-tokenizer2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/thhaus/nemotron4-tokenizer2/resolve/main/tokenizer.json
18.1 MB
- Xet hash:
- b8716bdf6571f7d42297eaba59e3c16ff3fd89e6547e41fc00d658e51e06c39f
- Size of remote file:
- 18.1 MB
- SHA256:
- eb85a97d4db94c9820e8e2477de974ce98039ae6ee3163e6bed8c3ec918b18e9
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