Real browser automation with local GLiNER2 inference and open weights. Work in progress. Contributions welcome.
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Updated
Sep 18, 2026 - Python
Real browser automation with local GLiNER2 inference and open weights. Work in progress. Contributions welcome.
Open-source alternative to TypeSafe's Jev: a System One style model layer that gives typed, calibrated decisions from any open-weights LLM in one forward pass (HF + vLLM), with honest benchmarks
MODA: open fashion retrieval benchmark and models by Hopit AI. MODA (203M, open source), MODA Pro Lite (213M, open weights), MODA Pro (hosted). Full-corpus benchmarks vs FashionSigLIP, SigLIP-SO400M and ZooClaw — one harness, losses shown. #1 open model on LookBench.
Hemmingway-1: a 27B model that writes the way a person writes. Open weights, free for non-commercial use (CC BY-NC 4.0); commercial use by agreement.
Curated Ideogram 4.0 prompts and image examples — typography, photorealistic portraits, product/UI mockups, and model comparisons. By Evolink.
Introducing Muse Glimmer: open-weight 30B agentic multimodal model that runs on your device (Meta). Interactive local agent lab + guide. Apache 2.0 · on-device AI · function calling
WicaraLLM is our Indonesian Small Language Model (56M parameters), built from scratch and trained on a 1.3B-token Indonesian corpus. Engineered to run efficiently on a single laptop GPU with just 6 GB of VRAM, it combines GQA, RoPE, SwiGLU, and RMSNorm, with supervised fine-tuning for conversational capabilities
A community-maintained catalog of open, low-filter, and community-reported AI video models, checkpoints, adapters, and endpoints.
OpenMayhem is an open-source and decentralized inference router for consumer & pro hardware. Providers earn, users/agents access cheap inference.
Companion code for the Manning book 'LLM Customization and Fine-Tuning.' Adapt open-weights LLMs end to end: prompting and RAG, LoRA/QLoRA, full SFT, distillation, and DPO/RLHF alignment.
One embedding space for text, image, video, audio, thermal, motion, and touch. Open weights, self-hostable.
Find what open-weight Large Language Model (LLM) can fit into your hardware and run it
Self-hosted, Jev-compatible decision-model API — one /v1/systemone endpoint, open weights (Laya, kev), one Docker image per engine.
A community-maintained catalog of open and low-filter AI image models, checkpoints, and local inference resources.
Structured YAML catalog of 4,587 AI models across 95 providers — pricing, context windows, modalities, capabilities. First-party data with TypeScript types and Zod validation.
Wald-Q4B: open-weight 4B decision model. Calibrated probability for every option, Jev-compatible /v1/systemone API, self-hosted. Weights on Hugging Face.
A field guide to running large language models on your own hardware — from a single laptop to a shared cluster. AI-drafted, human-reviewed.
A local launcher and platform for open-weight generative models. Install video, image and speech studios from their own repositories, run them on your Mac, and keep everything they make in one gallery.
Three small 4B language models for local decisions in English, Turkish and German. Jev-compatible API, per-option probabilities and CPU GGUF builds.
Open-weight only, video-aware podcast dubbing with ASR alignment, diarization, LLM translation, and voice-cloned TTS. Local inference.
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