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")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("zenlm/zen-router", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from zenlm/zen-router: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/zenlm/zen-router/resolve/main/tokenizer.json
- Command line
-
hf download hf://zenlm/zen-router/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/zenlm/zen-router/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- e0911b4a7dd7cdcfc13e63846d29a4799cc5979c035e6515a17cbf689c560fd5
- Size of remote file:
- 11.4 MB
- SHA256:
- df790baeb8e7f02fc5c3c40b7e9c558ef927284d77868375b5afd2f41bd0968f
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