Discussion
Search code, repositories, users, issues, pull requests...
iwhalen: Very cool stuff. Love the focus on CPU-first.Would also love to see some throughput numbers on basic VM setup.
deepsquirrelnet: Zero-shot encoder models are so cool. I'll definitely be checking this out.If you're looking for a zero-shot classifier, tasksource is in a similar vein.https://huggingface.co/tasksource/ModernBERT-large-nli
adsharma: Feels like it's written by ML people not following python software engineering practices.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
hbcondo714: There is another version at:https://github.com/urchade/GLiNERLooks like it’s still being maintained too?
adsharma: Use Gliner2. Much better model.
snthpy: This looks great. Thank you!
plaguna: Is this only for text I guess? What if the documents are in PDF? What is the recommendation to transform PDF to text?
fbilhaut: 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.
akreal: Docling: https://github.com/docling-project/docling
hbcondo714: Okay but there is a dependency on gliner1:https://github.com/fastino-ai/GLiNER2/issues/69
goodlux: gliner2 does classification as well as entities and relationships
