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Jina AI launches open-source 8k text embedding

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Re: Jina AI launches open-source 8k text embedding

#151

Post by EGreg »

szundi wrote: post #136
jerpint wrote: post #67

Earlier quoted context omitted.

It definitely is open source even if they don’t disclose all details behind the training

Interesting as the literal source of the result is not open

People need to realize something…

The model weights in eg TensorFlow are the source code.

It is not a von-Neumann architecture but a gigabyte of model weights is the executable part, no less than a gigabyte of imperative code.

Now, the training of the model is akin to the process of writing the code. In classical imperative languages that code may be such spaghetti code that each part would be intertwined with 40 others, so you can’t just modify something easily.

So the fact that you can’t modify the code is Freedom 2 or whatever. But at least you have Freedom 0 of hosting the model where You want and not getting charged for it an exorbitant amount or getting cut off, or having the model change out from under you via RLHF for political correctnesss or whatever.

OpenAI has not even met Freedom Zero of FSR or OSI’s definition. But others can.

Re: Jina AI launches open-source 8k text embedding

#153

Post by krageon »

jyrkesh wrote: post #125
abriosi wrote: post #115

Earlier quoted context omitted.

Imagine someone giving you a executable binary without the source code and calling it "open source"

I'm actually mostly in your camp here. But it's complicated with AI. What if someone gave you a binary and the source code, but not a compiler? Maybe not even a language spec? Or what if they gave you a binary and the source code and a fully documented language spec, and both of 'em all the way down to the compiler? BUT it only runs on special proprietary silicon? Or maybe even the silicon is fully documented, but pr…

There is the binary (the model) and the source (the thing that allows you to recreate the model, the dataset and methodology). Compilers and how art is made quite simply doesn't factor in here, because nobody is talking about the compiler layer. Art isn't even close to what is present. Trying to make this more complicated than it is is playing into companies' hands by troubling the waters around what constitutes open source.

Re: Jina AI launches open-source 8k text embedding

#154

Post by hboon »

simonw wrote: post #72
Grimburger wrote: post #70

Earlier quoted context omitted.

> Have links gone out of fashion? Yes. You wrote far more words than needed to answer the comment, I did it for you instead.

One of the reasons I write so much stuff is so I can provide links to things I've written to answer relevant questions.

Just to add that, we appreciate that very much.

Re: Jina AI launches open-source 8k text embedding

#155

Post by pietz »

I'm always happy to see OSS contributions but I don't quite understand why this model is so remarkable. As the leaderboard suggests it's ranking lower than OpenAI embeddings, while 14 other contributions are even better than that. Many of which feature a comparable or lower dimensionality than 768.

The 8k context window is new, but isn't the 512 token limitation a soft limit anyway? I'm pretty sure I can stuff bigger documents into BGE for example.

Furthermore, I think that most (all?) benchmarks in the MTEB leaderboard deal with very small documents. So there is nothing here that validates how well this model does on larger documents. If anything, I'd pick a higher ranking model because I put little trust in one that only ranks 17th on small documents. Should I expect it to magically get better when the documents get larger?

Plus, you can expect that this model was designed to perform well on the datasets in MTEB while the OpenAI model probably wasn't.

Many also stated that a 8k context embeddings will not be very useful in list situations.

When would anyone use this model?

Re: Jina AI launches open-source 8k text embedding

#157

Post by torginus »

magicalhippo wrote: post #130
losteric wrote: post #92

Earlier quoted context omitted.

The inference runtime software is open, the weights are an opaque binary. Publishing the training data, hyperparameters, process, etc - that would make the whole thing "open source".

The quake engine is still open source even though it doesn't come with the quake game assets, no? It seems unreasonable to require the training data just to be called open source, given it has similar copyright challenges as game assets. Of course, this wouldn't make the model reproducible. But that's different from open source.

It's a bit different - here most of the value lies in the weights.

A better analogy would be some graphics card drivers which ship a massive proprietary GPU firmware blob, and a small(ish) kernel shim to talk with said blob.

Re: Jina AI launches open-source 8k text embedding

#160

Post by jillesvangurp »

simonw wrote: post #21

I just shipped a new llm-embed-jina plugin for my LLM tool which provides access to these new Jina models: https://github.com/simonw/llm-embed-jina Here's how to try it out. First, install LLM. Use pip or pipx or brew: brew install llm Next install the new plugin: llm install llm-embed-jina You can confirm the new models are now available to LLM by running: llm embed-models You should see a list that includes "jina-e…

Thanks, this is wonderfully simple to use. Just managed to package this up using docker and was able to use it without a lot of drama. Nice how simple this is to use.

I've dabbled a bit with elasticsearch dense vectors before and this model should work great for that. Basically, I just need to feed it a lot of content and add the vectors and vector search should work great.

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