AI Infra2026
Ingests and normalizes security telemetry, runs multi-model AI agents to produce replayable investigations and automated triage/response; key features include a step-by-step Investigation Ledger, CI-gated eval harness, and self-hostable deployments.
AI Dataset2026
A prompt-only mixture of ~478k prompts designed to support antidoom-style generation and preference-data pipelines for reducing model repetition (doom loops). Prompts are stripped of answers and labels and sourced from many public datasets so it’s usable for FTPO/adapter generation but not for supervised QA evaluation.
AI Deploy2026
Runs local LLMs on Apple Silicon using native MTP speculative decoding to accelerate token generation while preserving the model's output distribution. Leverages the model's own MTP heads with batched verification and exact rejection sampling; ships with a Mac app, CLI, local OpenAI/Anthropic-compatible server, auto-tune, and Forge for building/verifying MTP adapters.
AI Dataset2026
Benchmarks LLM and VLM capabilities for toxicity-aware molecular editing using toxicity‑cliff molecule pairs. It provides QA-formatted tasks and CSV splits for fragment identification, non-toxic fragment generation, and detoxified molecule generation—useful for safety evaluation and drug-discovery research.
AI Dataset2026
A Chinese public-transit route-planning dataset for training and benchmarking LLMs that generate structured transit routes from origin–destination pairs. Releases include a large CPT corpus, SFT train/test splits, and a 30K real-world benchmark; anonymized and real testsets are provided for privacy-aware, fair evaluation.
AI Dataset2026
Provides 19,331 multi-turn ChatML Hermes reasoning traces produced by DeepSeek V4 Pro for LoRA fine-tuning of agent-style models; includes VRAM-tiered variants, train/valid/test splits, and dense tool-calling annotations in Parquet format.
AI Dataset2026
Provides 19,331 multi-turn ChatML Hermes reasoning traces for LoRA fine-tuning of local models to behave as Hermes agents. Includes train/valid/test splits, VRAM-tiered variants (nano→spark), ~138K tool-call annotations, and Parquet format under Apache-2.0.
AI Model2026
Mixture-of-Experts LLM tuned for mathematical and coding reasoning, with ~760M active / 8.4B total parameters and post-training for improved stepwise reasoning. Optimized for inference efficiency (vLLM/transformers forks) so it can run in computation-constrained or local deployments; Apache-2.0 licensed.
AI Dataset2026
Agentic coding evaluation dataset containing real-world, multi-step developer tasks and raw model responses across 20+ programming languages. Emphasizes challenging, persona-driven prompts for benchmarking and fine-tuning; users should filter and audit outputs before training.
AI Model2026
Merges Unsloth UD XL quantized GGUF of Qwen3.6-27B with compact Q8_0 MTP heads to enable multi-token (speculative) decoding on llama.cpp builds that support MTP; aimed at image-text-to-text usage with reduced MTP overhead.
AI Infra2026
High-throughput LLM inference engine for agentic workloads, combining a local‑SPMD static compiler for parallelism, a C++ scheduler with a Python execution plane and type‑safe KV‑cache reuse, pluggable high-performance kernels (including an MLA implementation), and a low‑overhead AsyncLLM entrypoint for production GPU inference.
AI Dataset2026
A retrieval benchmark suite focused on “oblique queries,” where relevance depends on latent attributes rather than surface keywords. Includes five tasks with large corpora, qrels (and pooled judgments), and task-specific constraints for evaluating embedding-based retrievers and reasoning-augmented retrieval.