AIBackends v0.8.1 adds GLiNER2.5-Decide local classification

Melvin Vivas · X post · 2026-09-25 · Open on X

Topics: LLMOps, Deployment & Monitoring, LLM Fundamentals · Level: intermediate

Summary

Release v0.8.1 of the creator's open-source library AIBackends adds support for Fastino's GLiNER2.5-Decide model. With it you can classify intent, routing, sentiment and policy in one local pass. You install it with the extraction extra.

Key points

• AIBackends v0.8.1 supports GLiNER2.5-Decide by Fastino Labs.
• GLiNER2.5-Decide handles intent, routing, sentiment and policy classification in one local pass.
• It runs locally, so no hosted LLM API is needed for these classification tasks.
• Install or upgrade: pip install -U "aibackends[extraction]".

Resources mentioned

• Releases · donvito/aibackends · repo · github.com · free
  Release notes for AIBackends, the creator's open-source Python library for running local AI backends.
• GLiNER2.5-Decide · tool · huggingface.co · free
  A 340M-parameter open-weight encoder model that answers user-defined typed questions and rules for fast, deterministic classification.
  Also in: Intent classification for support using GLiNER2.5-Decide notebook (Melvin Vivas on X · notes), Getting started with GLiNER2.5-Decide in a Colab notebook (Melvin Vivas on X · notes), GLiNER2.5-Decide: A 340M Encoder Model for Deterministic Classification (Melvin Vivas on X · notes)
• Fastino Labs (@fastinoAI) on X · person · x.com · free
  The X account of Fastino Labs, which builds GLiNER decision models and shares demos.
  Also in: GLiDE: Fastino's Decision Model with Adaptive Thinking (Melvin Vivas on X · notes), GLiDE by Fastino Labs: A Post-Trainable Reasoning Decision Model (Melvin Vivas on X · notes), GLiNER decision model demos from Fastino Labs (Melvin Vivas on X · notes), Intent classification for support using GLiNER2.5-Decide notebook (Melvin Vivas on X · notes) and 4 more

Try this

• Run pip install -U "aibackends[extraction]" to try GLiNER2.5-Decide classification.
• Build a local router that classifies incoming requests by intent and sentiment, and checks them against a policy, before sending them to the right handler.