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
File size: 605 Bytes
03d87f8 | 1 | {"base": "zenlm/zen-nano-0.6b", "tasks": ["code", "reasoning", "math", "creative", "vision", "long_context", "cheap_chat", "general"], "catalog": ["zen-nano-0.6b", "zen-agent-4b", "zen-coder-24b", "zen5-flash", "zen5", "zen5-coder", "zen5-max", "zen-omni", "zen-vl", "claude-opus-4-8", "claude-opus-4-5", "claude-opus-4-1", "claude-fable-5", "claude-sonnet-4-6", "claude-sonnet-4-5", "claude-haiku-4-5", "gpt-5.5", "gpt-5.4-mini", "gpt-5.2-pro", "gpt-5.1-codex-max", "o3", "gemini-3-pro", "gemini-3-flash", "grok-4", "deepseek-v3.2", "deepseek-reasoner", "kimi-k2", "minimax-m2"], "frozen_backbone": true} |