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.

Any chance you could wrap this in pyo3? There is a large python market for this.

Indeed. What's is interesting (and not so common) with models like GLiNER is that it is way lighter than LLMs while preserving good (if not better) quality and some zero-shot ability (in this case wrt to the entity classes). This feature is very significant, as most "traditional" (including Transformer-based) approaches are more or less supervised during fine-tuning. Icing on the cake, you don't have to deal with all the problems that arise when you want to get structured output from an LLM (in this case structured NER output).