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GitHub
AI Agent·2026
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TencentDB Agent Memory

Tencent Cloud (TencentDB Agent Memory Team)

Provides fully local long-term and symbolic short-term memory for AI agents via a 4-tier layered pipeline and Mermaid canvases, with zero external API dependencies. Key features: lossless drill-down from personas to raw traces, hybrid retrieval, and ready integrations for OpenClaw and Hermes.

#plugin#ai-agent#agent-skills#embeddings#nodejs+1
GitHub
AI Client·2026
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claude-obsidian

Agrici Daniel

Turns source documents into a linked, source-cited Obsidian wiki for grounded Q&A and research. Local-first vault workflows with content-addressed capture, provenance ledgers, BM25 retrieval, and Claude Code / Agent Skills integration.

#claude-code#agent-skills#plugin#github#llm+4
Hugging Face
AI Model·2026
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MiniMax-M2.7

MiniMaxAI

Text-generation LLM designed for agentic workflows: supports multi-agent 'Agent Teams', skill stacks and model self-evolution. Ships on Hugging Face with deployment guides (vLLM, Transformers, SGLang) and is positioned for engineering, tool-calling and productivity use cases.

#llm#huggingface#agent-skills#ai-agent#vllm+3
Hugging Face
AI Dataset·2026
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Jagle: Building a Large-Scale Japanese Multimodal Post-Training Dataset for Vision–Language Models

Issa Sugiura, Keito Sasagawa +9

Provides a ~9.2M-instance Japanese multimodal post-training dataset for vision–language models, combining image–text pairs, PDF corpora and generated VQA to improve Japanese VLM performance; access is restricted by Japanese copyright (download via llm-jp GitLab).

#multimodal#vision#ocr#llm#nlp+2
Hugging Face
AI Model·2026
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Nemotron-Labs-TwoTower-30B-A3B-Base-BF16

Fitsum Reda, John Kamalu +4·NVIDIA Corporation

Generates text by iteratively denoising blocks of tokens with a two-tower design: a frozen autoregressive context tower and a trainable diffusion denoiser tower, trading minimal quality loss for higher wall-clock throughput.

#nvidia#huggingface#transformers#pytorch#llm+4
Hugging Face
AI Dataset·2026
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Zero-to-CAD 1M

Mohammadmehdi Ataei, Farzaneh Askari +3

Provides one million executable, human-readable CadQuery construction sequences synthesized by an LLM-in-the-loop—each sample includes renders, STL/STEP exports, precomputed DINOv3 embeddings and a FAISS index. Designed for training and benchmarking text/image→3D and CAD-program generation models (Apache-2.0).

#huggingface#embeddings#llm#ai-agent#agent-skills+3
Hugging Face
AI Model·2026
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Hy3 preview

Tencent Hy Team

A Mixture-of-Experts instruct-capable LLM (295B total, 21B active) designed for long-context reasoning, code/agent workflows and instruction-following; released by Tencent Hy Team with safetensors weights on Hugging Face.

#llm#huggingface#vllm#ai-train#ai-agent+4
Hugging Face
AI Dataset·2026
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GLM-5.1-1000000x

Kassadin88

Provides 1,003,589 full chain-of-thought reasoning traces and final answers generated by GLM-5.1, split into main/Math/PHD-Science/Multilingual-STEM subsets. Useful for instruction-tuning, supervised fine-tuning, and reasoning experiments; released under Apache-2.0.

#huggingface#llm#nlp#math#science+1
Hugging Face
AI Model·2026
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MiniCPM-V 4.6

openbmb

Delivers an ultra-efficient, edge-friendly multimodal image-and-video-to-text model optimized for on-device deployment. Uses mixed 4x/16x visual token compression, a low-FLOPs visual encoder, and multiple quantized variants for mobile and embedded inference.

#multimodal#vision#video#mobile#android+6
Hugging Face
AI Model·2026
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Kimi K2.6

Moonshot AI (moonshotai)

Multimodal agent model for long-horizon coding, image-text understanding, and autonomous task orchestration. Built as a 1T-parameter Mixture-of-Experts with 256K context and native int4 quantization — intended for coding-driven design, persistent background agents, and swarm-style sub-agent workflows.

#foundation-model#llm#ai-agent#agent-skills#huggingface+5
Hugging Face
AI Dataset·2026
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Türkçe Atlas — Instruct SFT

AlicanKiraz0

Provides 336,146 Turkish instruction-following chat examples (system→user→assistant) for supervised fine-tuning; single train split (no validation/test), reported MIT license, diverse tasks (rewrites, summarization, QA) and a uniform system prompt that may bias model behavior.

#huggingface#nlp#llm#chatbot#json+3
Hugging Face
AI Model·2026
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Gemma 4 E4B — OBLITERATED v3

OBLITERATUS

Removes safety refusals from a Gemma 4 E4B–based model and publishes uncensored, locally runnable GGUF/safetensors variants while preserving all tensors and fixing prior corruption. Intended for red‑teaming and offline research; not recommended for production.

#huggingface#llm#nlp#ai-tools#chatbot+3
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