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France's homegrown open source online office suite

https://github.com/suitenumerique
310•nar001•3h ago•153 comments

British drivers over 70 to face eye tests every three years

https://www.bbc.com/news/articles/c205nxy0p31o
62•bookofjoe•46m ago•36 comments

Start all of your commands with a comma (2009)

https://rhodesmill.org/brandon/2009/commands-with-comma/
398•theblazehen•2d ago•143 comments

Hoot: Scheme on WebAssembly

https://www.spritely.institute/hoot/
71•AlexeyBrin•4h ago•14 comments

First Proof

https://arxiv.org/abs/2602.05192
22•samasblack•1h ago•14 comments

OpenCiv3: Open-source, cross-platform reimagining of Civilization III

https://openciv3.org/
762•klaussilveira•18h ago•237 comments

Reinforcement Learning from Human Feedback

https://arxiv.org/abs/2504.12501
46•onurkanbkrc•3h ago•3 comments

Stories from 25 Years of Software Development

https://susam.net/twenty-five-years-of-computing.html
21•vinhnx•2h ago•2 comments

The Waymo World Model

https://waymo.com/blog/2026/02/the-waymo-world-model-a-new-frontier-for-autonomous-driving-simula...
1013•xnx•1d ago•576 comments

Coding agents have replaced every framework I used

https://blog.alaindichiappari.dev/p/software-engineering-is-back
135•alainrk•3h ago•153 comments

Vocal Guide – belt sing without killing yourself

https://jesperordrup.github.io/vocal-guide/
150•jesperordrup•9h ago•56 comments

A Fresh Look at IBM 3270 Information Display System

https://www.rs-online.com/designspark/a-fresh-look-at-ibm-3270-information-display-system
12•rbanffy•4d ago•0 comments

Unseen Footage of Atari Battlezone Arcade Cabinet Production

https://arcadeblogger.com/2026/02/02/unseen-footage-of-atari-battlezone-cabinet-production/
97•videotopia•4d ago•24 comments

Making geo joins faster with H3 indexes

https://floedb.ai/blog/how-we-made-geo-joins-400-faster-with-h3-indexes
150•matheusalmeida•2d ago•40 comments

Show HN: Look Ma, No Linux: Shell, App Installer, Vi, Cc on ESP32-S3 / BreezyBox

https://github.com/valdanylchuk/breezydemo
257•isitcontent•19h ago•27 comments

Ga68, a GNU Algol 68 Compiler

https://fosdem.org/2026/schedule/event/PEXRTN-ga68-intro/
31•matt_d•4d ago•8 comments

Monty: A minimal, secure Python interpreter written in Rust for use by AI

https://github.com/pydantic/monty
270•dmpetrov•19h ago•144 comments

72M Points of Interest

https://tech.marksblogg.com/overture-places-pois.html
3•marklit•5d ago•0 comments

Hackers (1995) Animated Experience

https://hackers-1995.vercel.app/
536•todsacerdoti•1d ago•262 comments

Sheldon Brown's Bicycle Technical Info

https://www.sheldonbrown.com/
413•ostacke•1d ago•105 comments

Show HN: I spent 4 years building a UI design tool with only the features I use

https://vecti.com
356•vecti•21h ago•161 comments

What Is Ruliology?

https://writings.stephenwolfram.com/2026/01/what-is-ruliology/
60•helloplanets•4d ago•59 comments

Show HN: If you lose your memory, how to regain access to your computer?

https://eljojo.github.io/rememory/
329•eljojo•21h ago•201 comments

An Update on Heroku

https://www.heroku.com/blog/an-update-on-heroku/
453•lstoll•1d ago•297 comments

Microsoft open-sources LiteBox, a security-focused library OS

https://github.com/microsoft/litebox
368•aktau•1d ago•192 comments

Show HN: Kappal – CLI to Run Docker Compose YML on Kubernetes for Local Dev

https://github.com/sandys/kappal
13•sandGorgon•2d ago•3 comments

Cross-Region MSK Replication: K2K vs. MirrorMaker2

https://medium.com/lensesio/cross-region-msk-replication-a-comprehensive-performance-comparison-o...
7•andmarios•4d ago•1 comments

Female Asian Elephant Calf Born at the Smithsonian National Zoo

https://www.si.edu/newsdesk/releases/female-asian-elephant-calf-born-smithsonians-national-zoo-an...
58•gmays•14h ago•23 comments

How to effectively write quality code with AI

https://heidenstedt.org/posts/2026/how-to-effectively-write-quality-code-with-ai/
298•i5heu•21h ago•256 comments

Dark Alley Mathematics

https://blog.szczepan.org/blog/three-points/
108•quibono•5d ago•34 comments
Open in hackernews

Llama-Factory: Unified, Efficient Fine-Tuning for 100 Open LLMs

https://github.com/hiyouga/LLaMA-Factory
132•jinqueeny•4mo ago

Comments

Twirrim•4mo ago
https://llamafactory.readthedocs.io/en/latest/

I found this link more useful.

"LLaMA Factory is an easy-to-use and efficient platform for training and fine-tuning large language models. With LLaMA Factory, you can fine-tune hundreds of pre-trained models locally without writing any code."

yunohn•4mo ago
Is it a bug or are most documentation pages only available in ZH-CN and not EN?
tempodox•4mo ago
I’d say documentation that is only readable for those who know Chinese is a bug. You could open an issue to ask for translation if there isn’t one yet.
hall0ween•4mo ago
are there any use cases, aside from code generation and formatting, where fine-tuning consistently useful?
clipclopflop•4mo ago
Creating small, specialized models for specific tasks. Being able to leverage the up front training/data as a generalized base allows you to quickly create a small local model that can generate outputs for that task that can come close to or match the same you would see in a large/hosted model.
metadat•4mo ago
This reminds me conceptually of the Nvidia NIM factory where they attempt to optimize models in bulk / en-masse.

https://www.nvidia.com/en-us/ai/nim-for-manufacturing/

Word on the street is the project has yielded largely unimpressive results compared to its potential, but NV is still investing in an attempt to further raise the GPU saturation waterline.

p.s. This project logo stood out to me at presenting the Llama releasing some "steam" with gusto. I wonder if that was intentional? Sorry for the immature take but stopping the scatological jokes is tough.

tensorlibb•4mo ago
This is incredible! What gpu configs, budget to ultra high-end, would you recommend for local fine tuning?

Always curious to see what other ai enthusiasts are running!

spagettnet•4mo ago
axolotl is great on consumer hardware.
kelsey98765431•4mo ago
FYI it also supports pre-training, reward model training and RL, not just fine tuning (sft). My team built a managed solution for training that runs on top of llama factory and it's quite excellent and well supported. You will need pretty serious equipment to get good results out of it, think 8xh200. For people at home i would look at doing an sft of gemma3 270m or maybe a 1.6b qwen3, but keep in mind you have to have the dataset in memory as well as the model and kv-cache. cheers
spagettnet•4mo ago
depends ln your goals of course. but worth mentioning there are plenty of narrowish tasks (think text-to-sql, and other less general language tasks) where llama8b or phi-4 (14b) or even up to 30b with quantization can be trained on 8xa100 with great results. plus these smaller models benefit from being able to be served on a single a100 or even L4 with post training quantization, with wicked fast generation thanks to the lighter model.

on a related note, at what point are people going to get tired of waiting 20s for an llm to answer their questions? i wish it were more common for smaller models to be used when sufficient.

zwaps•4mo ago
Why do you have to keep the dataset in memory? We had good distributed streaming datasets for a good while now, no?
jcuenod•4mo ago
Can you compare this to Unsloth?
sabareesh•4mo ago
This is great,but most work is involved in curating the dataset and the objective functions for RL.
stefanwebb•4mo ago
There’s a similar library that also includes data synth and LLM-as-a-Judge: https://github.com/oumi-ai/oumi
BoorishBears•4mo ago
Yet another framework lying about Deepseek support.

I've been trying to actually finetune Deepseek (not distills) and there are few options

3abiton•4mo ago
Which version were you trying? Doesn't unsloth already support finetuning?
BoorishBears•4mo ago
Previous V3 base

Unsloth doesn't have an official multi-GPU story: there's hacked together solutions but they're finicky as it is for smaller models

In general Deepseek has very few resources on finetuning, that get even further muddied by people referring to the distills when they claim to be finetuning it.

edd25•4mo ago
This looks awesome! I've been struggling fine tuning using Discord messages from my server (for memes), issues with CUDA mostly. Will defo try this out!

On a side note, has anyone tried something similar? I have 100K messages and want to make a "dumb persona" which reflects the general Discord server vibe. I don't really care if it's accurate. What models would be most suitable for this task? My setup is not that powerful: 4070S, 32GB of RAM for training, Lenovo M715q for running with, Ryzen 5 PRO 2400GE, 16GB of memory.

Ambix•4mo ago
I've used this meta framework for LLM tuning, it really one of the best out there.