GLiNER is a really great research work. But putting this kind of things in production is just another job. Not trying to do self promotion here, but there are alternatives for this purpose, like gline-rs (https://github.com/fbilhaut/gline-rs). Support of GLiNER 2 models is on the way.
adsharma 17 hours ago [-]
Any chance you could wrap this in pyo3? There is a large python market for this.
iwhalen 1 days ago [-]
Very cool stuff. Love the focus on CPU-first.
Would also love to see some throughput numbers on basic VM setup.
GLiNER2 is an upgrade that allows for relationship extraction and classification, built on GLiNER, and added additional research / papers, then trained a new model.
No black, UV or ruff.
Prints messages with emojis to stdout by default.
Makes a connection to hugging face on every import.
https://github.com/fastino-ai/GLiNER2/pull/74
Would also love to see some throughput numbers on basic VM setup.
Edit: there are some latency numbers in the paper https://arxiv.org/pdf/2507.18546
If you're looking for a zero-shot classifier, tasksource is in a similar vein.
https://huggingface.co/tasksource/ModernBERT-large-nli
https://github.com/urchade/GLiNER
Looks like it’s still being maintained too?
https://github.com/fastino-ai/GLiNER2/issues/69