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:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Xenova/Kimi-K3-tokenizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: mit | |
| base_model: | |
| - moonshotai/Kimi-K3 | |
| library_name: transformers | |
| # Kimi K3 Tokenizer | |
| Standalone tokenizer files for Kimi K3. No custom tokenizer code or `trust_remote_code=True` is required. | |
| ## Transformers | |
| ```python | |
| from transformers import AutoTokenizer | |
| tokenizer = AutoTokenizer.from_pretrained("Xenova/Kimi-K3-tokenizer") | |
| inputs = tokenizer("Hello from Kimi K3!") | |
| ``` | |