Search: “framework”

New open source Jev like model for running on local devices from a group called Supersonic Labs. It's a 144M param local non-generative local classifier. From their site: Julia 1 opens our research in

Just wanted to share with someone - don't have much to report yet. I am interested in this new AliceAI model and have been wanting to make a community impact for a while - and releasing an initial age

Been building some multi-agent pipelines recently and the degradation in direct execution is insane. Whenever I pass a strict operational variable or hypothesis, the LLM triggers this 'Devil's Advocat

Source: Jev Benchmarks Its training method is literally called 'Reinforcement Learning for Calibrated Decisions.' Calibration gap vs human labels (lower = better): Yes/no: Jev 5.0, Gemini 3.8 Flash 2.

OpenAI’s decision to retire custom GPTs appears to rest on the assumption that Plugins, Skills, Projects, Apps, and Workspace Agents collectively replace their functionality. For many Small and Medium

GitHub: https://github.com/pfekin/LARA I've been working on LARA (Lightweight Additive Residual Adaptation), a research project on making post-training modular for frozen language models. I've also de

Repo here- https://github.com/Adudeguyman/ComfyUI-Fantastic-MiniMaxH3-PromptBuilder Alrighty, back again with an update to my (manual, no LLM connected) Fantastic MiniMax H3 Prompt Builder. Yeah it's

from internlm: We introduce Intern-S2-397B, our most capable multimodal foundation model for scientific intelligence and long-horizon agents. Intern-S2-397B scales along three critical dimensions: pre

i've been thinking about this more after trying different agent setups. the model isn't the only thing that determines how well an agent performs. The harness around the model matters a lot too. With

I don't think anyone posted about this here, but Qwen released a finetuned version of 3.5 4 for driving. The full Bf16 checkpoint is 9B. This is a very interesting development of Chinese AI labs tackl

I've hit again a point where me as a developer have to take a break from all this slop shit. Im a Developer for 13+ years and i loved it. But i fell for the slop trap. First it started with copilot an

Right, so this is going to be embarrassing but it's presumably something we've all been through at one point or another, and I guess this is my first time resolving something like this in the way that

https://village-sim-one.vercel.app/ - 16GB VRAM RTX 5070 Ti, fully offloaded - Vision on CPU - Windows, not headless - beellama.cpp - latest version with the kvarn performance enhancements making it a

Hi, everyone, I’ve just released VoxGen, a lightweight native inference engine for VoxCPM2, written in Rust and using Vulkan compute instead of Python/PyTorch/CUDA. Why VoxGen? The main reason I start

hi i make tool for this called llmog it's purpose to make llms free to - auto annotation datasets - reclassification existing yolo datasets running totally local using llama cpp or vllm or use externa

Been building AgentSwarms for a while. Agent platform with RAG, multi-agent workflows and a BI layer over your own data. Posting here because the whole thing runs without a single hosted API if you wa

I’ve been working on a small project called gemma4.c. The idea is pretty simple: you can download a modern language model, compile one 700-line C file, and have it generate text on an ordinary CPU. Th

Reposting here after sharing this on [r/MachineLearning](r/MachineLearning) a few days ago, where it got a much better response than I expected (300+ upvotes, great questions, zero roasting) GitHub is

Hey everyone! I wanted to share something I’ve been working on. I was inspired by projects from DeepMind and OpenAI, but noticed that most games are prohibitively difficult to integrate with an agent

Note: I use a Mac Studio M3U with 512 GB RAM, so this is not for everyone. I have been using antirez/ds4 with DS4 Flash for a few weeks now. Top quality, I am really impressed. This combination just d

Hey! Like a lot of people here with consumer GPUs (RTX 4060 8GB in my case), I wanted to see if I could use local models for daily coding tasks instead of burning cloud credits on simple boilerplate.

Over & over I see people post slop and excusing it as 'english is not my native language'. As if, if we could understand their language we'd see they wrote it all by hand Fine then, new rule: > if you

I want to build a PC/sever that can host me a ollama or alternative server, with good enough performance that it can be used for .net application development, specially with WinForms amd Blazor server

🧩 DeepSeek Harness v0.1 is now available in Developer Preview! 🔹 We’re opening it up to developers building agent harnesses worldwide and open-sourcing the codebase in MIT license. 🔹 Powered by the Co

Laid off then my partner of 10 years said he's leaving, have to move, etc... I will post the r/hardwareswap link when I make it. I'm willing to add some incentive for r/LocalLLaMA folks. I will also a

Spec-dec has been a thing for a while, in fact, it's wasn't an idea that was born for LLM inference. E.g. Uber's https://github.com/uber/submitqueue applied it to a merge queue. Apple & GDM had been r

First of all, I'm not a lab, this was a solo summer research project that finally culminated into the github repo and the writeup. The repo includes a much deeper dive with methods, findings about qua

Hi folks, I hate slop as much as you do, so instead of starting with 'The Problem', I'll just cut to the chase: I just published Lophius, which is the culmination of more than two years of fighting wi

I’m planning a dedicated home AI server, mainly for local LLM inference, agents/tool use, Docker services, and eventually larger MoE models with CPU offload. My plan is to start with 2x 16GB GPUs = 32

There are a lot of LLM benchmarks but few, if any, harness benchmarks. I am thinking this would be a really good community project to build one. End goal: a leaderboard of harness performance (multipl

I don't own a mac Right now, i want to buy one but its main job will be to host a Ollama or similar software to give me usable AI models in my network, since I don't want to pay for Cloude, GitHub cop

I deployed K3 on 32 H100s at work a couple of weeks ago and then got annoyed that there was no way to poke at it on my own machine. So I wrote an inference engine for it in C99. Nothing clever going o

TLDR below 👇🏼 I’ve seen a lot of hype around Qwen 3.6 35B and 3.5 120B lately, especially regarding coding and tool-use capabilities. On this subreddit it is the defacto recommended model for everyone

This post was not written by a clanker. Hey guys, I'm a comp sci major who wanted to introduce a cool project I built for quantizing models to ternary (1.58 bit) with as minimal of loss as possible, a

I saw u/danielhanchen's 1-bit Kimi K3 post: https://huggingface.co/unsloth/Kimi-K3-GGUF/discussions/12#6a6a4a90ec74ef13d85d7cf6 and decided to test Inkling-Small and Qwen3.6-27B myself, based on the f

I've been thinking about building a pipeline to generate reasoning training data for LLMs, but I want to avoid the common failure mode of synthetic data where you just generate the same template with

Greetings Community! 👋 I hope everyone is doing well! I'm Tauhid — Senior EEE student from a Bangladeshi University Today I'd like to share an open-source project I’ve been developing called P.A.I. (P

So, it appears that this is the week of open letters in AI🥲... an open letter signed by current and former employees of OpenAI, Anthropic and Google primarily - calling for a slow-down in frontier AI

TL;DR: Most RL post-training algorithms optimize the current batch and move on. But after an update, did the new policy actually become better? We introduce Policy Improvement Reinforcement Learning (

I've been working on an open-source workflow automation platform over the past few months, with Ollama as one of the first-class providers rather than treating it as an afterthought. The goal wasn't t

There is a lot of buzz around running 100B parameter models on cheap local hardware using ternary (1.58-bit) quantization like Microsoft's BitNet architecture. The theoretical hardware shortcuts are i

I have been running some experiments with smaller open-weight LLMs on multiple-choice questions of Swedish medical licensing exams. On a dataset called MedQA-SWE, GPT-4 scored 84% accuracy in 2024 and

At Bitwize, we've been building Logue, a native macOS app for AI meeting notes and writing, and we just open-sourced it (MIT). We're sharing it here because the whole point is that it runs 100% on-dev

HPD-Parsing: Hierarchical Parallel Document Parsing We introduce HPD-Parsing, a lightweight (1B) and high-throughput document parsing model built on a Hierarchical Parallel Decoding paradigm. Unified

Hi everyone, We've open-sourced Tri-Net v2, the official implementation accompanying our recently published Scientific Reports (Nature Portfolio) paper: 'Tri-Net: Unified Deep Learning for Skin Lesion

LLMs handle speech well once you run speech-to-text. They don't hear the rest: a bird outside, a glass breaking two rooms away, a smoke alarm two floors down. I've been working on an experimental open