dmezzetti

10 ms·

91.
by dmezzetti 2y ago
It was just updated last week. The dataset page on HF only has the scripts, the raw data resides over on Kaggle.
92.
by dmezzetti 2y ago
Hello - This is a great and accurate description. The idea is that out of the box there is a pipeline but each component is also customizable.
93.
by dmezzetti 2y ago
Interesting concept. But for a working system in C, why do we need to "convert" it to Rust. Seems like an effort where juice isn't worth the squeeze. Probably will create more problems than we're fixing.
94.
by dmezzetti 2y ago
If you're looking for a lightweight open-source framework designed to handle the patterns mentioned in this article: https://github.com/neuml/txtai Disclaimer: I'm the author of the framework.
95.
by dmezzetti 2y ago
We should wait until it's released before we anoint it. It's disheartening to see how we keep repeating the same pattern that gives in to hype over the scientific method.
96.
by dmezzetti 2y ago
Great news here. Will takes some time for it to trickle downstream but expect to see better vector embeddings models, entity extraction and more.
97.
by dmezzetti 2y ago
Very interesting, thanks for sharing!
98.
Annotate and Highlight Papers with LLMs(hub.docker.com)
3 points by dmezzetti 2y ago|0 comments
99.
by dmezzetti 2y ago
What was the error?
100.
Annotate and Highlight Papers with LLMs(pypi.org)
4 points by dmezzetti 2y ago|2 comments
101.
Show HN: AnnotateAI – Automatically annotate papers using LLMs(pypi.org)
3 points by dmezzetti 2y ago|1 comments
102.
by dmezzetti 2y ago
I've written two articles on this topic over the last few years: https://medium.com/neuml/grow-your-open-source-project-5b439... https://medium.com/neuml/grow-your-open-source-project-2-0-5...
103.
Show HN: txtai 8.1: Docling integration and Postgres/pgvector schema persistence(pypi.org)
1 points by dmezzetti 2y ago|0 comments
104.
txtai 8.1 released: Docling integration and Postgres/pgvector schema persistence(pypi.org)
1 points by dmezzetti 2y ago|0 comments
105.
by dmezzetti 2y ago
I fully agree. Postgres has solved many of the problems that many are re-solving with GenAI related databases. With txtai ( https://github.com/neuml/txtai ), I've went all in with Postgres + pgvector. Projects can s
106.
by dmezzetti 2y ago
This looks like an interesting project. Though it's worth noting that the license is AGPL. So if the idea is for this to take over for pgvecto.rs, it's an important data point for those building SaaS products. It will make pgvecto
107.
by dmezzetti 2y ago
An alternative you can try is txtai ( https://github.com/neuml/txtai ). RAG section: https://github.com/neuml/txtai?tab=readme-ov-file#retrieval-... Disclaimer: I'm the primary developer
108.
by dmezzetti 2y ago
No, it's using that in ensemble with a FFT and butter filters. WebRTC-VAD by itself didn't work that well.
109.
by dmezzetti 2y ago
Thanks for sharing. If you want notebooks that do some of this with local open models: https://github.com/neuml/txtai/tree/master/examples and here: https://gist.github.com/davidmezzetti
110.
by dmezzetti 2y ago
VAD is certainly a complex but underappreciated topic. If you like signal processing, FFTs and want to see a similar concept implemented in Python, then check out this code. It's has a fairly well-tuned VAD component built-in. https:&
111.
by dmezzetti 2y ago
txtai ( https://github.com/neuml/txtai ) has had inline vectorization since 2020. It supports Transformers, llama.cpp and LLM API services. It also has inline integration with LLM models and a built-in RAG pipeline.
112.
by dmezzetti 2y ago
It's like a time capsule of ordinary life. All the little moments when not many are watching and ironically now people are watching. Very fascinating!
113.
Extractous – Fast Text Extraction for GenAI with Rust and Apache Tika(github.com)
2 points by dmezzetti 2y ago|0 comments
114.
by dmezzetti 2y ago
Seeing a lot of Ollama vs running llama.cpp direct talk here. I agree that setting up llama.cpp with CUDA isn't always the easiest. But there is a cost to running all inference over HTTPS. Local in-program inference will be faster. Per
115.
Grow your open-source project 2.0(medium.com)
1 points by dmezzetti 2y ago|0 comments
116.
by dmezzetti 2y ago
Can we keep The Matrix out of training data? We don't want AI to see what the machines did there for an additional power source.
117.
Show HN: Analyzing Hugging Face Posts with Graphs and Agents(colab.research.google.com)
1 points by dmezzetti 2y ago|0 comments
118.
Analyzing Hugging Face Posts with Graphs and Agents(colab.research.google.com)
1 points by dmezzetti 2y ago|0 comments
119.
by dmezzetti 2y ago
Interesting project and approach, thanks for sharing! If you're interested in a simple solution to query a list with SQL including vector similarity, check this out: https://gist.github.com/davidmezzetti/f0a0b92f52
120.
by dmezzetti 2y ago
Excellent article on BM25! Author of txtai [1] here. txtai implements a performant BM25 index in Python [2] via the arrays package and storing the term frequency vectors in SQLite. With txtai, the hybrid index approach [3] supports both con

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