Early pretraining checkpoint of a compact multilingual causal LM aimed at low-memory deployment and Indic language support. Explores a Shared KV cache mode that can cut KV-cache memory by ~50% for inference; results are provisional (not a final, fully trained model).
Multilingual streaming ASR that transcribes 40 language-locales using a cache-aware FastConformer‑RNNT architecture. Supports language-ID prompting (or auto-detect), punctuation/capitalization, and configurable chunk sizes to trade latency vs. accuracy for production transcription and streaming voice agents.
W4A4-quantized build of a 25B-parameter multimodal LLM that produces text from image+text inputs and supports conversational tool use. Trades very small quality differences for much lower GPU memory and latency so inference can run on smaller accelerators (vLLM support).
A GGUF-format 9B LLM fine-tuned for code generation and agentic tool-calling that uses Multi-Token Prediction (MTP) and draft heads to increase throughput and long-range planning. Intended for local inference and research/experimental coding workflows; Apache‑2.0 license.
Provides a large-scale ASR corpus organized by normalized acoustic subsets for robustness training and evaluation. About 645,925 examples across 54 acoustic conditions (noise, echo, far-field, recording distortions) with many distortion/dropout/noise Parquet splits. Distributed as split Parquet files; license not specified on the dataset page.
Provides 9,000 reconstructed chain-of-thought (CoT) SFT examples produced by trace inversion from Claude Opus 4.6 outputs for fine-tuning reasoning-capable LLMs. Multilingual, packaged as .jsonl.gz and SFT/DPO-ready; verify numeric/code cases before training.
RL training dataset for long-context language-model fine-tuning with ~23K samples and nine reward types, provided in Parquet with bilingual ground-truth and reward metadata for direct RL/bench evaluation.
Supervised fine-tuning dataset of instruction-style examples in English and Chinese covering generation, QA, reasoning, math and code — targeted for SFT of 10–100B-parameter LLMs. Associated with arXiv:2602.09003; first published May 21, 2026.
Fine-tuned reasoning model that speeds up structured multi-step outputs using Multi-Token Prediction (MTP) from a Qwen3.6-27B base. Produces more concise, faster generations for coding, DevOps, math, and constrained-format tasks; experimental community release for research and evaluation.
Creator-centric benchmark for evaluating text-to-image models with 1,000 bilingual prompts and a 3-level, 56-facet taxonomy. Includes a trained Q-Judger judge model and leaderboard-ready evaluation scripts to surface gaps in real-world fidelity and creative generation.
Parallel Chinese→Vietnamese dataset of webnovel (xianxia) text provided in JSON for NMT training and teacher-student distillation. In-domain, ~100K–1M examples with CC-BY-4.0 license — useful for fine-tuning or distillation experiments but limited by narrow genre and small download footprint.
Instruction-tuned, unified Gemma 4 12B multimodal model that accepts text, image and audio inputs and generates text outputs locally. Encoder-free design reduces multimodal latency and fits on consumer devices while offering long-context support and native thinking/system-prompt features.