Builds structured knowledge graphs for retrieval-augmented generation via a multi-step GraphRAG pipeline that separates extraction from consolidation. Key features include typed two-stage extraction, DBSCAN-backed deduplication, LLM summarization, Leiden community detection, and a compact 7B extractor model (Meno-Lite-0.1).
Agentic coding and long-horizon text generation via a 118B-parameter Mixture-of-Experts LLM with a 1,048,576-token context window. Features 256 routed experts, native preserved-thinking (reasoning) control, speculative decoding draft models, and quantized checkpoints for lower-cost serving.
50,000 distilled conversational traces (≈120M tokens) generated from GLM-5.2 for high-reasoning text generation and QA, covering STEM, programming, creative and support dialogues; Apache-2.0 licensed.
Generates 2048-d multilingual text embeddings for retrieval and semantic search, suited for RAG and dense retrieval. Pruned and distilled from the Ministral-3 family into a ~1.14B BF16 model, supports long contexts (up to 32,768 tokens) and optimized for NVIDIA GPU inference.
Provides behavior-preserving next-step training traces from Claude Fable 5 for supervised fine-tuning and analysis of instruction-following, tool-calling, and coding agents. Runtime-normalized, independently verified, and supplied as Parquet/JSONL with 13,357 cumulative rows from 2,443 accepted trajectories.
Provides GGUF-quantized Inkling multimodal model weights for local image/audio-to-text and conversational inference. Includes quantization variants (example: 1-bit UD-IQ1_S), Apache-2.0 license, and compatibility with Unsloth Studio, vLLM and common inference stacks.
Evaluates retrievers and search agents on synthetic multi-hop questions that require assembling a complete set of supporting evidence. Provides English and Russian variants (395 questions each), a fixed dense index embedded with Qwen3-Embedding-8B, and BrowseComp-Plus evaluation integrations.
Accepts text, image and audio inputs and generates text outputs for conversational, instruction-following and multimodal tasks; a sparse-MoE autoregressive model (975B total, 41B active) with BF16/NVFP4 support and local-deploy recipes.
Provides live Codex-CLI agent run traces from GPT-5.6 Sol capturing coding, debugging, security reviews, and harness/seed workflows in cumulative next-action prefixes — suitable for supervised fine-tuning and analysis of tool-using coding agents.
Provides 324 Russian short-answer web-search tasks with gold supporting documents to evaluate fixed-index retrievers and search agents. Tasks span eight topical categories and five retrieval challenge types (multihop, structured evidence, temporal, entity disambiguation, comparative) and use a Qwen3-Embedding-8B index for evaluation.
Specialized LLM for clinical workflows trained via a human-gated self-evolution loop to improve patient consultation, multimodal clinical reasoning, interactive diagnosis, and EHR tool use. Iteratively refines targeted synthetic and curated data based on benchmark failures to raise specific capabilities without broad regressions.
Converts completed on-policy trajectories into natural-language 'hindsight skills' and converts the skill-induced action probability shifts into a dense token-level on-policy distillation signal, jointly optimized with outcome-based RL to improve sample efficiency and long-horizon agent behavior.