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As an open source maintainer, I can chime in on this.

With TxtAI, I've seen a large uptick in PRs (https://github.com/neuml/txtai/pulls?q=is%3Apr+is%3Aclosed+s...). While the extreme verbosity of Claude messages and commits is very annoying (plus the constant defending itself on why it's a bug), I do think it's a positive that more people are enabled.

It does require reviewing the PRs. Some can be tricky just like a human. For example I did merge this PR (https://github.com/neuml/txtai/pull/1136) and it would have completely broke search. But a human could also do that.

From an open source standpoint, I say the more the better. You just have to be willing to do the work to review and no not just having AI agents to review what the AI agents are submitting. There still needs to be a human in the loop, if you care about quality.


Very interesting project! Are there benchmarks for the "compatibility mode" or are all the numbers for the Gigatoken API?


Numbers are for the Gigatoken API, but compatibility mode just means eating a bunch of Python overhead (creating lists, reading strings to bytes). You can expect a modest ~200-300x speedup with compatibility mode depending on how you use it.


> a modest ~200-300x speedup with compatibility mode

marcelroed is modest, this speedup is not. Good work.


I can add some benchmarks for compatibility mode in the future. I have a little more juice to squeeze out of the Python interop though, so not quite ready for it yet.


The recent abrupt removal of the ability to see who has starred a project isn't a good move. Things like this certainly erode trust.

https://github.com/orgs/community/discussions/201209


I agree that Kokoro is a good TTS model.

If you're interested in an ONNX version and a permissively licensed TTS Tokenizer, I built a pipeline for that a while back: https://huggingface.co/NeuML/kokoro-base-onnx


100% agree on this.

I've been working on small local models for years with txtai (https://github.com/neuml/txtai). I've published close to 100 models that can run local for RAG, Agents, Vector Search and more (https://huggingface.co/NeuML/collections).


Interesting project. Happy to see someone who shares an interest in tiny vector embeddings models. I've worked on tiny (1MB - 4MB, 250K - 950K parameters) embeddings models called BERT Hash https://huggingface.co/blog/NeuML/bert-hash-embeddings

Keep up the great work!


Why does HN let OpenAI and Anthropic basically advertise but it throws down the gauntlet at a small developer like myself when we do "self promotion"?

Top 3 posts as of this moment are all about Claude.


Local models are great for a lot of things past just software development. We need to move towards solving other real world problems vs just building software. I've been focused on that with TxtAI (https://github.com/neuml/txtai) for 6 years now.


Well-Read Students Learn Better: On the Importance of Pre-training Compact Models

Related paper that's a good read: https://arxiv.org/abs/1908.08962


They have paid hosting - https://huggingface.co/enterprise and paid accounts. Also consulting services. Seems like a pretty good foundation to me.


and a lot of traction on paid (private in particular) storage these days; sneak peek at new landing page: https://huggingface.co/storage


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