nheko
axolotl
nheko | axolotl | |
---|---|---|
18 | 29 | |
1,766 | 5,811 | |
1.2% | 9.3% | |
9.6 | 9.8 | |
8 days ago | 6 days ago | |
C++ | Python | |
GNU General Public License v3.0 only | 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.
nheko
- Shutting down the letsblock.it project and its official instance
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PSA: security vulnerability in qBitorrent 4.5.x webUI
Look at this, notice anything different? https://github.com/Nheko-Reborn/nheko/issues/new/choose
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This Year in Matrix
Nheko has been around for a number of years. Never used it myself though.
https://github.com/Nheko-Reborn/nheko
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Matrix was worth the effort to self host.
Matrix clients hit different than pretty much any other chat client I've use before. Theres multiple clients I've found like nheko, moments, element that are a pleasure to look at and smooth as hell. Even better you can have users use web services like Element Web to sign-up and chat. Its sick.
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What flatpaks are "official" (i.e., directly from the application's developer)?
The Nheko flatpak is official. Just compare the source to the nightlies we build and upload to our nightly repo.
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GTK4 Matrix Client
Like almost every client out there it has no support for e2ee. I was happy to find https://nheko-reborn.github.io (I'm a KDE user so Qt apps are preferred).
- Mozilla Thunderbird Beta now supports Matrix chat
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weed rule
There's also FluffyChat or Nheko if Element is too heavy.
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Using Files with Browsers, in Reality
I probably wouldn't have guessed that `e.dataTransfer.items` gets cleared at the first await (since I'm not a proficient web developer), but I would've been extremely wary of this code in general. Additionally (not tied to async-await but race conditions in general), is `item.getAsFileSystemHandle()` a TOCTTOU vulnerability where the type of an item can change between folders and files and symlinks etc., while this code is running?
Rust's & vs. &mut system largely eliminates shared state hazards in both threading and asynchronity (&mut is exclusive/unaliased and can't be mutated by other threads or event loop jobs, and & is difficult and unidiomatic to mutate), though it doesn't solve async cancellation errors (https://carllerche.com/2021/06/17/six-ways-to-make-async-rus..., discussed at https://news.ycombinator.com/item?id=27542504), or filesystem TOCTTOU (https://blog.rust-lang.org/2022/01/20/cve-2022-21658.html as well as user code).
Qt event loop reentrancy is fun(tm) as well. It looks like a blocking call, but spawns a nested event loop which can do anything (but rarely enough to lull you into a false sense of complacency), resulting in segfaults like https://github.com/Nheko-Reborn/nheko/issues/656 (workaround at https://github.com/Nheko-Reborn/nheko/commit/570d00b000bd558..., I didn't look into it). And Qt lacks "easy" await syntax and a framework based on calling red functions (though I didn't look into C++20 coroutines yet, perhaps https://www.qt.io/blog/asynchronous-apis-in-qt-6 or https://github.com/mhogomchungu/tasks or https://blog.blackquill.cc/asynchronous-qtquick-uis-and-thei...?).
- Introducing Native Matrix VoIP with Element Call!
axolotl
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Ask HN: Most efficient way to fine-tune an LLM in 2024?
The approach I see used is axolotl with QLoRA using cloud GPUs which can be quite cheap.
https://github.com/OpenAccess-AI-Collective/axolotl
- FLaNK AI - 01 April 2024
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LoRA from Scratch implementation for LLM finetuning
https://github.com/OpenAccess-AI-Collective/axolotl
- Optimized Triton Kernels for full fine tunes
- Axolotl
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Let’s Collaborate to Build a High-Quality, Open-Source Dataset for LLMs!
One option is to look at what Axolotl uses. They have a list of different dataset formats that they support. They're mostly in JSON with specific field names, so you could start putting a dataset together with a text editor or a JSON editor.
- Axolotl: Streamline fine-tuning of AI models
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Dataset Creation Tools?
You can save that overall set into a json file and load it up as training data in whatever you're using. I'm using axolotl for it at the moment. Though a GUI based option is probably best for the first couple of tries until you get a feel for the options.
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Progress on Reproducing Phi-1/1.5
Looking forward to the results! If it turns out the dataset is reproducible, then it might be a good candidate for ReLora training on axolotl!
What are some alternatives?
gomuks - A terminal based Matrix client written in Go.
signal-cli - signal-cli provides an unofficial commandline, JSON-RPC and dbus interface for the Signal messenger.
axolotl - A Signal compatible cross plattform client written in Go, Rust and Vuejs
gpt-llm-trainer
Signal-Android - Patches to Signal for Android removing dependencies on closed-source Google Mobile Services and Firebase libraries. In branches whose names include "-FOSS". Uses new "foss" or "gms" flavor dimension: build with "./gradlew assemblePlayFossProdRelease".
LoRA - Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
weechat-matrix - Weechat Matrix protocol script written in python
mlc-llm - Enable everyone to develop, optimize and deploy AI models natively on everyone's devices.
telegram-bot-api - Telegram Bot API server
LMFlow - An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All.
org.signal.Signal
koboldcpp - A simple one-file way to run various GGML and GGUF models with KoboldAI's UI