Uses Parallel Looped Transformers (PLT) to make loop count a practical knob for code models, finding two loops give the best test-time gains. Trains 7B models on 18T tokens and attributes saturation beyond two loops to a gain–cost tradeoff from positional mismatch.
Provides FP8-quantized weights of GLM-5.2 — a 744B long-context LLM tuned for sustained 1M-token engineering, coding and agentic workflows; compatible with vLLM, Transformers, SGLang and Ascend NPU deployments.
Provides a harness that lets language models control embodied manipulation via iterative perception–reasoning–action loops, semantic action abstractions, and multimodal observations. Demonstrates distilling capabilities into a 4B open-source model with under 2K simulated trajectories and shows sim-to-real generalization.
Proposes ZPPO, a distillation method that keeps the teacher inside prompts rather than injecting teacher gradients, using binary- and negative-candidate prompts plus a prompt replay buffer to recover learning signal on hard examples; shows gains for small Qwen3.5 students across 31 multimodal benchmarks.
Provides 1.8M synthetic Belgian personas (1.2M records; 300k per language) in Dutch/French/German/English, grounded in Belgian census distributions to improve representativeness for LLM training and evaluation. Includes 23 persona and contextual fields, CC BY 4.0 license, produced with NeMo Data Designer.
Provides GGUF-quantized GLM-5.2 builds for local text-generation with a solid 1M-token context, dynamic 1-/2-bit quant options, and Unsloth runtime integrations — targeted at long-horizon coding, reasoning and agent workflows. MIT licensed.
Contains 603 coding and math prompt–response pairs produced by Claude Fable‑5 (generated 2026-06-10), provided as a JSONL subset for fine-tuning, evaluation, and behavior analysis. Responses are 'non-thinking' (no chain-of-thought); small, anonymized, and lacking an explicit license.
Evaluates multimodal LLMs' ability to reconstruct past observations and act in controllable non-Markov games. Introduces RNG-Bench with two games (Matching Pairs, 3D Maze), three controllable difficulty axes, a head-to-head duel protocol, and a Memory Gap metric to separate forgetting from action errors.
Provides pre-parsed arXiv LaTeX source files aligned with official metadata as ready-to-query Parquet rows. Bundles each paper's .tex/.bib/.sty etc. into a single readable tree, updates monthly, and simplifies large-scale access for LLM pretraining, document understanding, and citation analysis while requiring adherence to original arXiv licenses.
Self‑hosted A‑share quantitative workbench for screening, monitoring, backtesting and stock-level analysis using TickFlow data; supports 18 Polars strategies, vectorbt backtesting, realtime rule-based alerts, pluginable data sources and optional LLM-driven strategy generation and stock analysis.
A local, quantized Gemma 4 12B fine-tune packaged as GGUF quants that runs on ~4.5 GB VRAM. Optimized for coding and multi-step agentic tool use (read→reason→act→verify), ships multiple quant sizes (Q3_K_M–Q8_0) and MTP draft support; English-centric with trade-offs versus generalist models.
Provides a deduplicated 2.0M-row corpus of FABLE.5 / Mythos agent traces with row-level provenance and session-limit rows removed. Includes canonical Parquet and gzip JSONL exports, SHA256 row hashes, and provenance fields for tracing first-source datasets.