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Tags: LLM tools
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1–17 of 17 · Most stars

DeepSeek 4 Flash and PRO local inference engine for Metal, CUDA and ROCm

Translated🎭 277 plug-and-play AI expert roles — supporting 20 tools such as Claude Code/Cursor/Copilot, covering 20 departments including engineering/design/marketing/finance. Includes 64 original agents for the Chinese market (Xiaohongshu/Douyin/WeChat/Feishu/DingTalk/Qt host computer software/mechanical design). Paired with the orchestrator agency-orchestrator, a single sentence lets multiple experts collaborate automatically as a DAG.

TranslatedLangGPT: Empowering everyone to become a prompt expert! 🚀 📌 Proposer of Structured Prompt 📌 Initiator of Meta-Prompt 📌 The most popular paradigm for putting prompts into practice | Language of GPT The pioneering framework for structured & meta-prompt design 10,000+ ⭐ | Battle-tested by thousands of users worldwide Created by 云中江树 (Yunzhong Jiangshu, "river and trees amid the clouds")

The fast, precise document-intelligence engine for every language: text, tables and metadata from 100+ formats, with OCR, transcription and code intelligence.

  • text-extraction
  • document-intelligence
  • metadata-extraction
  • pdf-extraction

Steering-first neuron explorer for Qwen3.5-4B: push every MLP neuron, keep every rollout, browse the results

  • interpretability
  • mechanistic-interpretability
  • qwen
  • steering

A computer, compiled into the weights of a language model. An exact CPU inside Qwen3.5-4B, with Gated DeltaNet state as RAM.

  • gated-deltanet
  • interpretability
  • llm
  • qwen

Run a 105 GB AI model on a Mac that can't hold it. Qwen3.8-Flash-Next 4-bit, streamed from SSD on 16–64 GB Apple Silicon Macs. Fully native Swift, MLX and Metal. Offline, no Python. CLI, Swift library, and Ollama/OpenAI/Anthropic APIs. Works with Claude Code and Codex.

Build AI text detectors whose decisions are mechanistically grounded and human-auditable (EMNLP 2026)

  • ai-text-detection
  • explainable-ai
  • interpretability
  • mechanistic-interpretability

Kubernetes operator for self-hosted LLM inference across a heterogeneous GPU fleet: NVIDIA CUDA, AMD Vulkan, and Apple Silicon Metal. Runtimes: llama.cpp, vLLM, TGI, mlx-server. Multi-GPU sharding, model caching, OpenAI-compatible endpoints. Apache-2.0, run across homelab and on-prem fleets, actively developed.

DecisionPivot: a diagnostic benchmark for decision models in LLM systems. Contrast pairs that differ in one decisive detail, generators with independent solvers, scorer and runners.

  • benchmark
  • calibration
  • decision-making
  • evaluation