Tribuo
hyperfine
Tribuo | hyperfine | |
---|---|---|
15 | 74 | |
1,226 | 20,020 | |
0.6% | - | |
4.8 | 8.1 | |
3 days ago | 6 days ago | |
Java | Rust | |
Apache 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Tribuo
- FLaNK Weekly 08 Jan 2024
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Is deeplearning4j a good choice?
It seems to have been picked up by Eclipse and there is also Oracle Labs' Tribuo and Deep Java Library. All seem active, but I don't know much about any of them. I agree it's probably best to follow the community and use a more popular tool like PyTorch.
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Stochastic gradient descent written in SQL
We built model & data provenance into our open source ML library, though it's admittedly not the W3C PROV standard. There were a few gaps in it until we built an automated reproducibility system on top of it, but now it's pretty solid for all the algorithms we implement. Unfortunately some of the things we wrap (notably TensorFlow) aren't reproducible enough due to some unfixed bugs. There's an overview of the provenance system in this reprise of the JavaOne talk I gave here https://www.youtube.com/watch?v=GXOMjq2OS_c. The library is on GitHub - https://github.com/oracle/tribuo.
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Just want to vent a bit
Although it may be a bit more work, you can do both machine learning and AI in Java. If you are doing deep learning, you can use DeepJavaLibrary (I do work on this one at Amazon). If you are looking for other ML algorithms, I have seen Smile, Tribuo, or some around Spark.
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Anybody here using Java for machine learning?
We've been developing Tribuo on Github for two years now, MS are very actively developing ONNX Runtime (and the Java layer is fairly thin and wrapped over the same C API they use for node.js and C#), and things like XGBoost and LibSVM have been around for many years and the Java bits are developed in tree with the rest of the code so updated along with it. Amazon have a team of people working on DJL, though you'd have to ask them what their plans are.
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Java engineer wants to be a researcher
FWIW, Oracle actually did release a Java ML library - https://github.com/oracle/tribuo.
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txtai 3.4 released - Build AI-powered semantic search applications in Java
Tribuo (tribuo.org, github.com/oracle/tribuo). ONNX export support is there for 2 models at the moment in main, there's a PR for factorization machines which supports ONNX export, and we plan to add another couple of models and maybe ensembles before the upcoming release. Plus I need to write a tutorial on how it all works, but you can check the tests in the meantime.
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Hottest topics for research for JAVA software engineers
You can do ML & data science in Java (full disclosure: I help run TensorFlow-Java, I maintain ONNX Runtime's Java interface, and I'm the lead developer on Oracle Labs' Java ML library Tribuo, so I'm pretty biased). It tends not to be as favoured in research, though I've published academic ML papers which used Java implementations. People do deploy ML models quite a bit in Java in industry.
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John Snow Labs Spark-NLP 3.1.0: Over 2600+ new models and pipelines in 200+ languages, new DistilBERT, RoBERTa, and XLM-RoBERTa transformers, support for external Transformers, and lots more!
It might be worth having a look at the ONNX Runtime Java API in addition to TF-Java, it'll let you deploy the rest of the HuggingFace pytorch models that don't have TF equivalents. I built the Java API a few years ago, and it's now a supported part of the ONNX Runtime project. We use it in Tribuo to provide one of our text feature embedding classes (BERTFeatureExtractor).
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If it gets better w age, will java become compatible for machine learning and data science?
The IJava notebook kernel works pretty well for data science on top of Java. We use it in Tribuo to write all our tutorials, and if you've got the jar file in the right folder everything is runnable. For example, this is our intro classification tutorial - https://github.com/oracle/tribuo/blob/main/tutorials/irises-tribuo-v4.ipynb.
hyperfine
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Measuring startup and shutdown overhead of several code interpreters
Check out the official hyperfine Github repo
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Bun - The One Tool for All Your JavaScript/Typescript Project's Needs?
And then I used hyperfine to run the benchmarks on my MacBook Pro 14 M2 Max, and here are the results:
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Faster tetranucleotide (k-mer) frequencies!
Search "benchmarking tools for linux" and decide that hyperfine is good for what I'm doing. Run Jennifer's new python script against my refactored perl and find that the python is 1.26 times faster for k=3 and 1.47 times faster for k=4. For the Covid-19 sequence, these are both on the order of hundreds of milliseconds.
- Hyperfine: A command-line benchmarking tool
- FLaNK Weekly 08 Jan 2024
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Show HN: Inshellisense – IDE style shell autocomplete
> It is very possible to write sub 100ms procedures in TS, […]
I will not disagree with this statement because I don’t have a way to test inshellisense right now. Could you (or anyone with a working Node + NPM installation) please install inshellisense and post the actual numbers? Perhaps using a tool like hyperfine (https://github.com/sharkdp/hyperfine).
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Firefox has surpassed Chrome on Speedometer
Yeah, while it's not as thorough as these tools, the method is at least reproducible and sane, and with ~10 or so samples, you get an interval with a nice confidence.
Another through method will be hyperfine[0], yet I wanted to provide a method which requires no installation and can be done in a whim, without jumps and hoops, with the tools already at hand.
[0]: https://github.com/sharkdp/hyperfine
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How to optimize your config? What are mistakes to avoid when optimizing your config?
That is native and inbuild but I would suggest below options instead 1. Using lazy's Profile tab instead https://github.com/folke/lazy.nvim 2. Using a dedicated plugin to do this https://github.com/dstein64/vim-startuptime. 3. Using an external program hyperfine is one that I use https://github.com/sharkdp/hyperfine
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How to remove all <br> from all of my .html files
Fair enough, although might I recommend using hyperfine for your testing? ;p
What are some alternatives?
Deep Java Library (DJL) - An Engine-Agnostic Deep Learning Framework in Java
criterion.rs - Statistics-driven benchmarking library for Rust
Deeplearning4j - Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learning using automatic differentiation.
fd - A simple, fast and user-friendly alternative to 'find'
oj! Algorithms - oj! Algorithms
ripgrep - ripgrep recursively searches directories for a regex pattern while respecting your gitignore
spark-nlp - State of the Art Natural Language Processing
awesome-mac - Now we have become very big, Different from the original idea. Collect premium software in various categories.
txtai - 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
kubeconform - A FAST Kubernetes manifests validator, with support for Custom Resources!
grobid - A machine learning software for extracting information from scholarly documents
quinn - Async-friendly QUIC implementation in Rust