Instructions to use zenlm/zen-router with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zenlm/zen-router with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zenlm/zen-router")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("zenlm/zen-router", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": null, | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|im_end|>", | |
| "errors": "replace", | |
| "is_local": true, | |
| "local_files_only": false, | |
| "max_length": 512, | |
| "model_max_length": 131072, | |
| "pad_to_multiple_of": null, | |
| "pad_token": "<|im_end|>", | |
| "pad_token_type_id": 0, | |
| "padding_side": "right", | |
| "split_special_tokens": false, | |
| "stride": 0, | |
| "tokenizer_class": "Qwen2Tokenizer", | |
| "truncation_side": "right", | |
| "truncation_strategy": "longest_first", | |
| "unk_token": null | |
| } | |