setfit
Graal
setfit | Graal | |
---|---|---|
13 | 156 | |
1,990 | 19,788 | |
3.7% | 0.4% | |
9.2 | 10.0 | |
3 days ago | 7 days ago | |
Jupyter Notebook | Java | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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.
setfit
- FLaNK Stack 05 Feb 2024
- Smarter Summaries with Finetuning GPT-3.5 and Chain of Density
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[Discussion] Convince me that this training set contamination is fine (or not)
It did, sorry for the hasty edits! I removed that part b/c I realized that there isn't a compelling-enough reason for me to believe that text similarity is clearly inappropriate. In fact, you can train the Pr(condition | chat) classifier I suggested above using similarity training! Use SetFit for that. In the end you'll get a classifier and a similarity model.
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Ask HN: What's the best framework for text classification (few-shot learning)?
[3] https://github.com/huggingface/setfit
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Is it worth using LLMs like GPT-3 for text classification?
There's also kinda related approaches like SetFit which calculate embeddings from pretrained transformer models then then fit a classifier on top of the embeddings. I've yet to try it but it supposedly works well with very few labelled examples.
- LLMs for Text Classification (7B parameters)
- GPT-3 vs GPT-Neo / GPT-J for startup classification
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Ideas on how to improve classification and scoring using Mean Pooled Sentence Embeddings
You could have a look at setfit.
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SetFit (Sentence Transformer Fine-tuning) - Fewshot Learning without prompts [D]
Found relevant code at https://github.com/huggingface/setfit + all code implementations here
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Most Popular AI Research Sept 2022 - Ranked Based On Total GitHub Stars
Efficient Few-Shot Learning Without Prompts https://github.com/huggingface/setfit https://arxiv.org/abs/2209.11055v1
Graal
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Java 23: The New Features Are Officially Announced
Contrary to what vocal Kotlin advocates might believe, Kotlin only matters on Android, and that is thanks to Google pushing it no matter what.
https://spectrum.ieee.org/the-top-programming-languages-2023
https://snyk.io/reports/jvm-ecosystem-report-2021/
And even so, they had to conceed Android and Kotlin on their own, without the Java ecosystem aren't really much useful, thus ART is now updatable via Play Store, and currently supports OpenJDK 17 LTS on Android 12 and later devices.
As for your question regarding numbers, mostly Java 74.6%, C++ 13.7%, on the OpenJDK, other JVM implementations differ, e.g. GraalVM is mostly Java 91.8%, C 3.6%.
https://github.com/openjdk/jdk
https://github.com/oracle/graal
Two examples from many others, https://en.wikipedia.org/wiki/List_of_Java_virtual_machines
- FLaNK Stack 05 Feb 2024
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Apple releases Pkl – onfiguration as code language
Pkl was built using the GraalVM Truffle framework. So it supports runtime compilation using Futurama Projections. We have been working with Apple on this for a while, and I am quite happy that we can finally read the sources!
https://github.com/oracle/graal/tree/master/truffle
Disclaimer: graalvm dev here.
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Live Objects All the Way Down: Removing the Barriers Between Apps and VMs
That's pretty interesting. It's not as aggressive as Bee sounds, but the Espresso JVM is somewhat similar in concept. It's a full blown JVM written in Java with all the mod cons, which can either be compiled ahead of time down to memory-efficient native code giving something similar to a JVM written in C++, or run itself as a Java application on top of another JVM. In the latter mode it obviously doesn't achieve top-tier performance, but the advantage is you can easily hack on it using all the regular Java tools, including hotswapping using the debugger.
When run like this, the bytecode interpreter, runtime system and JIT compiler are all regular Java that can be debugged, edited, explored in the IDE, recompiled quickly and so on. Only the GC is provided by the host system. If you compile it to native code, the GC is also written in Java (with some special conventions to allow for convenient direct memory access).
What's most interesting is that Espresso isn't a direct translation of what a classical C++ VM would look like. It's built on the Truffle framework, so the code is extremely high level compared to traditional VM code. Details like how exactly transitions between the interpreter/compiled code happen, how you communicate pointer maps to the GC and so on are all abstracted away. You don't even have to invoke the JIT compiler manually, that's done for you too. The only code Espresso really needs is that which defines the semantics of the Java bytecode language and associated tools like the JDWP debugger protocol.
https://github.com/oracle/graal/tree/master/espresso
This design makes it easy to experiment with new VM features that would be too difficult or expensive to implement otherwise. For example it implements full hotswap capability that lets you arbitrarily redefine code and data on the fly. Espresso can also fully self-host recursively without limit, meaning you can achieve something like what's described in the paper by running Espresso on top of Espresso.
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Crash report and loading time
I'm also using GraalVM if that's of any help.
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Quarkus 3.4 - Container-first Java Stack: Install with OpenJDK 21 and Create REST API
Quarkus is one of Java frameworks for microservices development and cloud-native deployment. It is developed as container-first stack and working with GraalVM and HotSpot virtual machines (VM).
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Level-up your Java Debugging Skills with on-demand Debugging
Apologies, I didn't mean to imply DCEVM went poof, just that I was sad it didn't make it into OpenJDK so one need not do JDK silliness between the production one and the "debugging one" since my experience is that's an absolutely stellar way to produce Heisenbugs
And I'll be straight: Graal scares me 'cause Oracle but I just checked and it looks to the casual observer that it's straight-up GPLv2 now so maybe my fears need revisiting: https://github.com/oracle/graal/blob/vm-23.1.0/LICENSE
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Rust vs Go: A Hands-On Comparison
> to be compiled to a single executable is a strength that Java does not have
I think this is very outdated claim: https://www.graalvm.org/
- Leveraging Rust in our high-performance Java database
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Java 21 makes me like Java again
https://github.com/oracle/graal/issues/7182
What are some alternatives?
iris - Transformers are Sample-Efficient World Models. ICLR 2023, notable top 5%.
Liberica JDK - Free and 100% open source Progressive Java Runtime for modern Javaâ„¢ deployments supported by a leading OpenJDK contributor
whisper - Robust Speech Recognition via Large-Scale Weak Supervision
Adopt Open JDK - Eclipse Temurinâ„¢ build scripts - common across all releases/versions
VToonify - [SIGGRAPH Asia 2022] VToonify: Controllable High-Resolution Portrait Video Style Transfer
awesome-wasm-runtimes - A list of webassemby runtimes
motion-diffusion-model - The official PyTorch implementation of the paper "Human Motion Diffusion Model"
SAP Machine - An OpenJDK release maintained and supported by SAP
git-re-basin - Code release for "Git Re-Basin: Merging Models modulo Permutation Symmetries"
maven-jpackage-template - Sample project illustrating building nice, small cross-platform JavaFX or Swing desktop apps with native installers while still using the standard Maven dependency system.
storydalle
wasmer - 🚀 The leading Wasm Runtime supporting WASIX, WASI and Emscripten