Direktori skill
Setiap rekomendasi tetap terhubung dengan repositori, audit, dan jalur pemasangannya.
Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website to learn more about our enterprise grade Platform product for production grade workflows, partitioning, enrichments, chunking and embedding.
AI powered open source recommender system engine supports classical/LLM rankers and multimodal content via embedding
A highly extensible Markdown editor. Version control, AI Copilot, mind map, documents encryption, code snippet running, integrated terminal, chart embedding, HTML applets, Reveal.js, plug-in, and macro replacement.
Find related notes and excerpts while writing. Your link building copilot displays relevant content in graph + list view. A local embedding model powers semantic search. Zero setup. No API key.
Semantic search over videos using Gemini Embedding 2 or Qwen3-VL.
MTEB: Massive Text Embedding Benchmark
Fast, Accurate, Lightweight Python library to make State of the Art Embedding
Fine-tune LLMs on your Mac with Apple Silicon. SFT, DPO, GRPO, Vision, TTS, STT, Embedding, and OCR fine-tuning — natively on MLX. Unsloth-compatible API.
Unify Efficient Fine-tuning of RAG Retrieval, including Embedding, ColBERT, ReRanker.
Agent Skill for building evidence-backed Markdown knowledge bases with zero-cost setup, image-aware capture, automatic wiki maintenance, and an interactive knowledge graph—without requiring a RAG stack or Obsidian.
100+ Chinese Word Vectors 上百种预训练中文词向量
Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.
Direktori skill
Setiap rekomendasi tetap terhubung dengan repositori, audit, dan jalur pemasangannya.
Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website to learn more about our enterprise grade Platform product for production grade workflows, partitioning, enrichments, chunking and embedding.
AI powered open source recommender system engine supports classical/LLM rankers and multimodal content via embedding
A highly extensible Markdown editor. Version control, AI Copilot, mind map, documents encryption, code snippet running, integrated terminal, chart embedding, HTML applets, Reveal.js, plug-in, and macro replacement.
Find related notes and excerpts while writing. Your link building copilot displays relevant content in graph + list view. A local embedding model powers semantic search. Zero setup. No API key.
Semantic search over videos using Gemini Embedding 2 or Qwen3-VL.
MTEB: Massive Text Embedding Benchmark
Fast, Accurate, Lightweight Python library to make State of the Art Embedding
Fine-tune LLMs on your Mac with Apple Silicon. SFT, DPO, GRPO, Vision, TTS, STT, Embedding, and OCR fine-tuning — natively on MLX. Unsloth-compatible API.
Unify Efficient Fine-tuning of RAG Retrieval, including Embedding, ColBERT, ReRanker.
Agent Skill for building evidence-backed Markdown knowledge bases with zero-cost setup, image-aware capture, automatic wiki maintenance, and an interactive knowledge graph—without requiring a RAG stack or Obsidian.
100+ Chinese Word Vectors 上百种预训练中文词向量
Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.
Direktori skill
Setiap rekomendasi tetap terhubung dengan repositori, audit, dan jalur pemasangannya.
Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website to learn more about our enterprise grade Platform product for production grade workflows, partitioning, enrichments, chunking and embedding.
AI powered open source recommender system engine supports classical/LLM rankers and multimodal content via embedding
A highly extensible Markdown editor. Version control, AI Copilot, mind map, documents encryption, code snippet running, integrated terminal, chart embedding, HTML applets, Reveal.js, plug-in, and macro replacement.
Find related notes and excerpts while writing. Your link building copilot displays relevant content in graph + list view. A local embedding model powers semantic search. Zero setup. No API key.
Semantic search over videos using Gemini Embedding 2 or Qwen3-VL.
MTEB: Massive Text Embedding Benchmark
Fast, Accurate, Lightweight Python library to make State of the Art Embedding
Fine-tune LLMs on your Mac with Apple Silicon. SFT, DPO, GRPO, Vision, TTS, STT, Embedding, and OCR fine-tuning — natively on MLX. Unsloth-compatible API.
Unify Efficient Fine-tuning of RAG Retrieval, including Embedding, ColBERT, ReRanker.
Agent Skill for building evidence-backed Markdown knowledge bases with zero-cost setup, image-aware capture, automatic wiki maintenance, and an interactive knowledge graph—without requiring a RAG stack or Obsidian.
100+ Chinese Word Vectors 上百种预训练中文词向量
Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.
Direktori skill
Setiap rekomendasi tetap terhubung dengan repositori, audit, dan jalur pemasangannya.
Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website to learn more about our enterprise grade Platform product for production grade workflows, partitioning, enrichments, chunking and embedding.
AI powered open source recommender system engine supports classical/LLM rankers and multimodal content via embedding
A highly extensible Markdown editor. Version control, AI Copilot, mind map, documents encryption, code snippet running, integrated terminal, chart embedding, HTML applets, Reveal.js, plug-in, and macro replacement.
Find related notes and excerpts while writing. Your link building copilot displays relevant content in graph + list view. A local embedding model powers semantic search. Zero setup. No API key.
Semantic search over videos using Gemini Embedding 2 or Qwen3-VL.
MTEB: Massive Text Embedding Benchmark
Fast, Accurate, Lightweight Python library to make State of the Art Embedding
Fine-tune LLMs on your Mac with Apple Silicon. SFT, DPO, GRPO, Vision, TTS, STT, Embedding, and OCR fine-tuning — natively on MLX. Unsloth-compatible API.
Unify Efficient Fine-tuning of RAG Retrieval, including Embedding, ColBERT, ReRanker.
Agent Skill for building evidence-backed Markdown knowledge bases with zero-cost setup, image-aware capture, automatic wiki maintenance, and an interactive knowledge graph—without requiring a RAG stack or Obsidian.
100+ Chinese Word Vectors 上百种预训练中文词向量
Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.