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The Path to Mojo 1.0

https://www.modular.com/blog/the-path-to-mojo-1-0
1•tosh•1m ago•0 comments

Show HN: I'm 75, building an OSS Virtual Protest Protocol for digital activism

https://github.com/voice-of-japan/Virtual-Protest-Protocol/blob/main/README.md
3•sakanakana00•4m ago•0 comments

Show HN: I built Divvy to split restaurant bills from a photo

https://divvyai.app/
3•pieterdy•6m ago•0 comments

Hot Reloading in Rust? Subsecond and Dioxus to the Rescue

https://codethoughts.io/posts/2026-02-07-rust-hot-reloading/
3•Tehnix•7m ago•1 comments

Skim – vibe review your PRs

https://github.com/Haizzz/skim
2•haizzz•8m ago•1 comments

Show HN: Open-source AI assistant for interview reasoning

https://github.com/evinjohnn/natively-cluely-ai-assistant
3•Nive11•9m ago•4 comments

Tech Edge: A Living Playbook for America's Technology Long Game

https://csis-website-prod.s3.amazonaws.com/s3fs-public/2026-01/260120_EST_Tech_Edge_0.pdf?Version...
2•hunglee2•12m ago•0 comments

Golden Cross vs. Death Cross: Crypto Trading Guide

https://chartscout.io/golden-cross-vs-death-cross-crypto-trading-guide
2•chartscout•15m ago•0 comments

Hoot: Scheme on WebAssembly

https://www.spritely.institute/hoot/
3•AlexeyBrin•18m ago•0 comments

What the longevity experts don't tell you

https://machielreyneke.com/blog/longevity-lessons/
2•machielrey•19m ago•1 comments

Monzo wrongly denied refunds to fraud and scam victims

https://www.theguardian.com/money/2026/feb/07/monzo-natwest-hsbc-refunds-fraud-scam-fos-ombudsman
3•tablets•24m ago•0 comments

They were drawn to Korea with dreams of K-pop stardom – but then let down

https://www.bbc.com/news/articles/cvgnq9rwyqno
2•breve•26m ago•0 comments

Show HN: AI-Powered Merchant Intelligence

https://nodee.co
1•jjkirsch•28m ago•0 comments

Bash parallel tasks and error handling

https://github.com/themattrix/bash-concurrent
2•pastage•28m ago•0 comments

Let's compile Quake like it's 1997

https://fabiensanglard.net/compile_like_1997/index.html
2•billiob•29m ago•0 comments

Reverse Engineering Medium.com's Editor: How Copy, Paste, and Images Work

https://app.writtte.com/read/gP0H6W5
2•birdculture•35m ago•0 comments

Go 1.22, SQLite, and Next.js: The "Boring" Back End

https://mohammedeabdelaziz.github.io/articles/go-next-pt-2
1•mohammede•40m ago•0 comments

Laibach the Whistleblowers [video]

https://www.youtube.com/watch?v=c6Mx2mxpaCY
1•KnuthIsGod•42m ago•1 comments

Slop News - The Front Page right now but it's only Slop

https://slop-news.pages.dev/slop-news
1•keepamovin•46m ago•1 comments

Economists vs. Technologists on AI

https://ideasindevelopment.substack.com/p/economists-vs-technologists-on-ai
1•econlmics•48m ago•0 comments

Life at the Edge

https://asadk.com/p/edge
4•tosh•54m ago•0 comments

RISC-V Vector Primer

https://github.com/simplex-micro/riscv-vector-primer/blob/main/index.md
4•oxxoxoxooo•58m ago•1 comments

Show HN: Invoxo – Invoicing with automatic EU VAT for cross-border services

2•InvoxoEU•58m ago•0 comments

A Tale of Two Standards, POSIX and Win32 (2005)

https://www.samba.org/samba/news/articles/low_point/tale_two_stds_os2.html
4•goranmoomin•1h ago•0 comments

Ask HN: Is the Downfall of SaaS Started?

4•throwaw12•1h ago•0 comments

Flirt: The Native Backend

https://blog.buenzli.dev/flirt-native-backend/
3•senekor•1h ago•0 comments

OpenAI's Latest Platform Targets Enterprise Customers

https://aibusiness.com/agentic-ai/openai-s-latest-platform-targets-enterprise-customers
2•myk-e•1h ago•0 comments

Goldman Sachs taps Anthropic's Claude to automate accounting, compliance roles

https://www.cnbc.com/2026/02/06/anthropic-goldman-sachs-ai-model-accounting.html
4•myk-e•1h ago•5 comments

Ai.com bought by Crypto.com founder for $70M in biggest-ever website name deal

https://www.ft.com/content/83488628-8dfd-4060-a7b0-71b1bb012785
1•1vuio0pswjnm7•1h ago•1 comments

Big Tech's AI Push Is Costing More Than the Moon Landing

https://www.wsj.com/tech/ai/ai-spending-tech-companies-compared-02b90046
6•1vuio0pswjnm7•1h ago•0 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.