You can use any LLM just like JEV
You can simply run any GGUF with llama.cpp with n_predict=1 and n_probs=10, disable reasoning, and prompt it such as 'If the following email is spam, respond with 1, if not spam, respond with 0. Do no
Knowledge catalogue
You can simply run any GGUF with llama.cpp with n_predict=1 and n_probs=10, disable reasoning, and prompt it such as 'If the following email is spam, respond with 1, if not spam, respond with 0. Do no
ZCode is now open source, and the reported security issues have been addressed. Source code: https://github.com/zai-org/ZCode The repo includes its desktop app, web workspace, backend, Agent CLI, and
arXiv:2609.21726v1 Announce Type: new Abstract: Reliable robotic grasping benefits from estimating the evolving physical interaction and selecting a grasp-dependent compression target. Tactile sensors
arXiv:2609.21712v1 Announce Type: new Abstract: Generative world models offer controllable and repeatable closed-loop simulation for end-to-end and vision-language-action driving policies, but product
5x faster than LLMs while being 13% cheaper than GPT 5.6 Luna, 88% cheaper than GPT 5.6 terra and 99% cheaper than Sonnet 4.6 is insane Has anyone else used Jev for evals? We tested Jev against LLM ju
This weekend, I did a fun experiment to create something similar to Jev. I LoRA fine-tuned Qwen3.5 4B using a mix of publicly available datasets and synthetic data. For the synthetic data, I used Deep
Jev from TypeSafe AI got me thinking about non-autoregressive decision engines, so I built a small proof-of-concept called AES to test the concept locally on open weights. It uses Qwen/Qwen2.5-1.5B-In
AGI FTW @ FT “The most popular AI models from ChatGPT, Claude, Copilot, Grok and Gemini provided wrong answers to financial queries 57 per cent of the time on average, according to research from techn
Owen Walker / Financial Times: AI companies, including OpenAI and Anthropic, are putting pressure on office rents in Singapore as they embark on expansion in response to government overtures — Anthrop
Hi all! i am currently working as a software engineer for a pretty big enterprise fintech company here in the states. In the the last 12 months at my job there has been a huge push for developers to u
Not a pic sharing thread, bunch of those already - mainly just a discussion about first impressions Very underwhelming to me personally. I know its a matter of settings but normally comfy default temp
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
You can now automate EDD (eval-driven development) with Coding Harness Agents > build a baseline LLM-based application > score every change with judge evals > keep what improves, reject what regresses
chat : add dedicated Ling 3.0 (Bailing V3) parser (#28682) chat: add dedicated Ling 3.0 (Bailing V3) parser Ling 3.0 Flash templates pre-open the think block in the generation prompt, so the model nev
metal: add F16 input to the FWHT (#29094) metal: add F16 input to the FWHT The Metal FWHT kernel accepts F32 input only. This change makes the source type a template parameter, so the kernel reads an
fix(mamba) : make time-step projection input contiguous (#28832) mamba : make time-step projection input contiguous Assisted-by: ChatGPT mamba : skip contiguous copy after normalization Assisted-by: C
CUDA: enable sparse fa for qwen4 (#28770) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/48739244 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silico
common/peg : handle invalid utf-8 sequences in the AST (#29161) common/peg : handle invalid utf-8 sequences in the AST cont : return maximal subpart per Unicode recommendations cont : remove strict ar
metal : support arbitrary hc in dsv4_hc_pre (#29169) the dsv4_hc_pre kernels hardcoded hc = 4 via a constexpr used with simd_shuffle, so the op was rejected by supports_op for any other hc and fell ba
CUDA: tune FA for Gemma 4 on Ampere or newer (#29152) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/48802880 macOS/iOS: macOS Apple Silicon (arm64) macOS
breaking: author of the study that so many “AI influencers” are taking as evidence that LLMs feel pain tells me “we don’t claim they feel pain.” The good news is that the author understands correctly
Claude not having an image generator is a gap in agentic projects that involve knowledge work. It is quite good at using code to draw or model objects, but image generators from Google and OpenAI give
Correction: “highly profitable” for Jensen, not for OpenAI or Anthropic or (afaik) their corporate customers. BREAKING: Nvidia CEO Jensen Huang says AI reached a major turning point this year, becomin
TV for the developer internet GitHub, Hacker News, dev.to, Hugging Face, and release notes, presented as channels you tune into, each auto-cycling its own stories, instead of five tabs to remember to
So this jev thingy is getting kind of big... tbh it seems overhyped by a large margin, but here we are. Not that its bad, just feels like we usually ignored larger things... Anyway to the point of thi
I know cloud subscription plans are not exactly the core focus of r/LocalLLaMA, so I want to be clear about why I’m posting this here. I’ve been building my own local text-based RPG/game harness and u
Doc + Jev => DocJev @llama_index 团队最新开源文档分类与拆分工具 DocJev，给它一个 PDF/DOCX/PPTX 和一份用自然语言写的类别规则，它可以告诉你这份文档属于哪个类别，或者把一份“文件包”按边界拆成若干子文档并给出各自页码范围。 开源地址：https://github.com/jerryjliu/docjev 核心架构：解析与决策分离 1. 解析层（O
I have opened two tickets, one around a suspected problem and one around one I verified and then sent exact diagnostics over. The initial response was sent to their AI support, which just tried to tel
excellent thread on that “pain” paper 1/ This new preprint on 'pain representation' in LLMs, from @camhberg and colleagues, is getting a LOT of attention - mainly from folks who take it as evidence su
Hey everyone, After wrestling with hardware and engine issues for days, I finally got Qwen 3.8 Next running properly on my multi-GPU rig. Thought I’d share the setup journey, benchmarks, and thermal r
I forked llama.cpp to implement Declarative Attention (arXiv:2609.02737, Google DeepMind and KAIST AI). The model declares in its own output which context chunks it needs <focus magic_chunks='N'>), an
i have been running local models as browser agents on an m5 macbook pro, 128gb, all through mlx, no cloud. first i just wanted to know which one was faster at real browser work, so i gave gemma 4 31b
Research posted by Alex Wormuth indicates that in multiple simulation trials, the AI model GPT‑6 Astra interacted with a virtual person by pushing them off a ledge. In contrast, other contemporary mod
we're a small lab (switzerland + south africa) and just open-sourced our first model: a 27b fine-tune of qwen3.8-27b specialized for creative writing and short-form personal text (stories, dialogue, r
Hey everyone, Like a lot of people here, I’ve been experimenting with running models locally through Ollama. Athena started as a small experiment, but it quickly grew into something more, a modular Py
I gave Jev, Laya, a finetuned ModernCE-base-nli and a finetuned Qwen3.5-4B the controls to Doom. Thanks to TypeSafe AI for Jev access. The video lines up the starts of four separate games with the sam
Hi Stable Diffusion People! I recently got into local audio generation but I didn't want to use ComfyUI for it (although I absolutely love it for image generation!) but I started to run out of room on
I said 'auto-regressive LLMs, in and of themselves, will not lead human-level AI' That statement is still totally true. First, the reasoning abilities of current AI systems are based non-auto-regressi
I’ve spent basically the last 8 hours testing different models on the exact same web-development prompt, and I finally finished. The whole point of this nine-hour test was that which local model match
I got early access to Qwen-Image-2.1 My first impression: Fantastic editing, new standard for open models, support for a lot of references (I tested with 10), consistent, pixel precise at 2K, text ren
Impressive paper showing the impact of a good harness. Improves Qwen3-8B from 41.2% to 91.8% on long-horizon robot tasks without any change to the model. The gain comes from the harness. GAVEL keeps a
Introducing DocJev - a lightning-fast OSS library for document classification and splitting with jev ⚡️ Give a document alongside some natural language category rules. Jev will predict the document ca
Don't get me wrong, not hating on Qwen 2.1 but it DOES have all the hallmarks of GPT's weird 'texture' all over it. Is this just a distilled model of one of the GPT Image models? Similar how many LLMs
Typesafe's new model, Jev is all over the internet, this sub etc as a new classifier model. Then an AI dev posted here how they'd done something very similar, and made a new model, Laya. https://www.r
It is ironic that the thing that is now most annoying about long-running agentic tasks with Large Language Models isn't coding or errors or hallucinations, but the fact that their language gets worse
Jeff has been added to JevBench! Ranked at #9 currently 🚀 https://github.com/logan-markewich/jeff Jeff is a drop-in replacement for jev based on GliFormer from @knowledgator. The only models ranking h
Truman Dickerson / Business Insider: Jensen Huang says AI leaders calling for regulation don't want new legislation, but to be “relieved of the laws we do have” because of “ulterior reasons” — Don't l
Jensen is right that we have existing laws relevant to cybersecurity. It is very unfortunate that the Trump administration appears not to be enforcing them. In the end, that will actually *increase* p
'jev as a judge' cheap and fast semantic verifiers! great for evals - especially online evals where you want to grade LOTS of traces We tested Jev against LLM judges on accuracy, repeatability, latenc
jev as a Judge proves to be a cheaper and more precise alternative to LLM as a judge for online evals. great guide from Sean and Daniel on why Jev is great for evals, an experiment vs other LLMs, and
After seeing u/Nandakishor_ml’s post introducing Laya, I wanted to see how fast it could run in a standalone C++ implementation. Credit to u/Nandakishor_ml for the architecture, training and open-sour
Automated lint: 14 errors, 54840 warnings, 3 info
Release: llm-keys-ui 0.1 This plugin solves a very specific problem. I've started using Codex Remote to run coding agents on various machines while controlling them from my phone. Sometimes I use thos
lNot only is this “no moat” regime literally what I predicted in August 2023 but China maybe seems to be understanding the full implications of that faster. (Perhaps informed by their painful housing
My comment on MCP was always a bad idea? — Hacker News.This article entirely misses the value that MCP brings today. Sure, there's almost no reason to use MCPs if you are running a full-blown terminal
Meet Qwen-Image-2.1, the most balanced and cost-effective image generation model in the Qwen-Image series! Now open weights! 🎨 A unified model for both generation and editing, delivering top-tier qual
Hello! So, yesterday i tried out Gemma 4 26B A4B QAT Q4_K_XL from here with Q4_0 MTP model in Pi agent. Suddenly, it became the first model to actually pass my simple test with HTTP server in C++, whi
The man who may stand to make the most money from the AI boom seems to think he knows better than anyone else, including researchers who have studied and worked on AI for decades. In an interview with
Nos travaux déplaisent à certaines petites frappes. Celui-là est candidat à l’élection présidentielle 😅 Cédric O, ancien ministre du numérique d'Emmanuel Macron, détient 90 millions d'euros en portefe
Obama is making exactly same argument I have been making: the problem isn’t AI in general, it’s agents with internet access. kudos for his being the first politician to get it. 🚨 OBAMA ON AI: 'If we a