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Contents

GitHub
AI Agent·2026
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Centaur

Paradigm, Tempo

Runs shared, self-hosted AI agents in isolated Kubernetes sandboxes accessible from Slack or an API. Provides durable workflows, reusable tool plugins, and network-edge credential injection (iron-proxy) so agents can execute real work securely and audibly for teams.

#ai-agent#agent-skills#rust#python#ai-workflow+6
Hugging Face
AI Dataset·2026
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Voices in the Wild

zhifeixie

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.

#audio#speech#ASR#multilingual#voice+1
Large Language Model Papers·2026
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DataPrep-Bench: Benchmarking LLMs as Training Data Preparators

Hao Liang, Qifeng Cai +12

Measures how well LLMs and agent-driven workflows prepare supervised training data end-to-end by jointly benchmarking data construction and data-quality evaluation across six domains, using a downstream-grounded protocol and new metrics.

#LLM#benchmarks#evaluation#agent-skills#ai-train+5
Hugging Face
AI Dataset·2026
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Jackrong/Claude-opus-4.7-TraceInversion-5000x

Jackrong

Dataset of 5,000 reconstructed chain-of-thought samples produced by trace‑inversion from Claude‑opus‑4.7 summaries — packaged for SFT/DPO fine‑tuning. Key features: reconstructed CoT traces, multilingual prompts, gzip .jsonl format. Best used for reasoning distillation and model-level supervision; synthetic traces may need extra verification.

#llm#nlp#huggingface#claude#transformers+2
Hugging Face
AI Dataset·2026
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Jackrong/claude-opus-4.6-traceInversion-9000x

Jackrong

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.

#huggingface#llm#nlp#multilingual#pandas+4
Hugging Face
AI Model·2026
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Qwen3.6 27B - OBLITERATED

OBLITERATUS

Provides a locally runnable 26.9B Qwen3.6 checkpoint that surgically reduces refusal behavior in weight space while preserving capability; ships bfloat16 safetensors and a GGUF quant ladder for local runtimes and red-team evaluation.

#huggingface#transformers#llm#vllm#ai-deploy+5
GitHub
AI Infra·2026
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Switchyard

NVIDIA Corporation, NVIDIA-NeMo

Routes LLM API traffic across providers by translating OpenAI, Anthropic, and OpenAI Responses formats, and orchestrates multi-backend routing with typed algorithms and Prometheus metrics. A Rust proxy/library offering launcher, standalone server, and embeddable routing components; experimental (pre-alpha).

#rust#llm#ai-serving#ai-api#ai-api-management+9
Hugging Face
AI Dataset·2026
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GoLongRL (Kwai-Klear)

Kwai-Klear

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.

#huggingface#RL#LLM#NLP#paper+2
Hugging Face
AI Audio·2026
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MOSS-Transcribe-Diarize

OpenMOSS-Team, MOSI.AI +1

Converts long-form multi-speaker audio/video into a compact, speaker-aware transcript with timestamps and anonymous speaker labels in one pass. Combines ASR and diarization in a single model, supports custom prompts/hotwords, and targets meetings, podcasts, interviews and long recordings.

#ASR#audio#speech#stt#transformers+5
GitHub
AI Train·2026
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Cosmos-Framework

NVIDIA

End-to-end Python framework for training and serving NVIDIA's Cosmos world models (Cosmos3), integrating distributed training (FSDP/TP/CP/PP), DCP/safetensors checkpoints, dataset adapters, multiple inference backends, online serving, and agent skills.

#nvidia#ai-train#ai-serving#pytorch#cuda+8
Hugging Face
AI Dataset·2026
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openbmb/UltraData-SFT-2605

openbmb

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.

#llm#huggingface#multilingual#math#code+4
Hugging Face
AI Model·2026
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Qwopus3.6-27B-v2-MTP

Jack Rong (Jackrong)

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.

#huggingface#transformers#llm#ai-train#ai-inference+5
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