Instructions to use Xenova/Kimi-K3-tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Xenova/Kimi-K3-tokenizer with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Xenova/Kimi-K3-tokenizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Xenova/Kimi-K3-tokenizer: direct link, hf CLI and curl.
- Browser
- Download file 19.6 MB
-
https://huggingface.co/Xenova/Kimi-K3-tokenizer/resolve/main/tokenizer.json
- Command line
-
hf download hf://Xenova/Kimi-K3-tokenizer/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Xenova/Kimi-K3-tokenizer/resolve/main/tokenizer.json
19.6 MB
- Xet hash:
- 13658510f0636496ceec1f425f79711ea38bda7221966f3e4dacd388e7e73950
- Size of remote file:
- 19.6 MB
- SHA256:
- b55c4532c501114da9a8891b77d244fa32eee2ace2bd51abb5dc4fb156f60eb9
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