Fine-tuning ModernBERT-base as a task router (quote post)

Melvin Vivas · X post · 2026-09-18 · Open on X

Topics: Fine-tuning & Model Customization, AI Agents, Tool Use & MCP · Level: intermediate

Summary

The creator adds 'awesome' to his own post about fine-tuning ModernBERT-base. The quoted post describes training a classifier that decides whether a task goes to Astra or Luna. The idea is a small encoder model used as a router between models or agents.

Key points

• ModernBERT-base is a small encoder model that can be fine-tuned for sequence classification.
• Training goal: classify incoming tasks and delegate each one to either Astra or Luna.
• A cheap classifier in front of larger models can act as a model/agent router.

Resources mentioned

• ModernBERT-base · tool · huggingface.co · free
  An open-source modernized BERT encoder model. The quoted post uses it as the speed baseline for LFM2.5-Encoder.
  Also in: Train Your Own LLM Model Router by Fine-Tuning ModernBERT as a Classifier (Melvin Vivas on X · notes), Free Colab Notebooks: ModernBERT, Gemma QLoRA, GLiNER & Guardrails (Melvin Vivas on X · notes), Fine-Tune ModernBERT-base as a Task-Routing Classifier (Melvin Vivas on X · notes), Train ModernBERT as a Prompt Router Between Two Models (Colab Notebook) (Melvin Vivas on X · notes) and 2 more

Try this

• Fine-tune ModernBERT-base to classify tasks and route each one to one of two models or agents.