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Contents

Hugging Face
AI Model·2026
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Laguna S 2.1

Poolside

Agentic coding and long-horizon text generation via a 118B-parameter Mixture-of-Experts LLM with a 1,048,576-token context window. Features 256 routed experts, native preserved-thinking (reasoning) control, speculative decoding draft models, and quantized checkpoints for lower-cost serving.

#llm#vllm#transformers#huggingface#ai-coding+2
Hugging Face
AI Dataset·2026
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GLM-5.2 Conversation

ianncity

50,000 distilled conversational traces (≈120M tokens) generated from GLM-5.2 for high-reasoning text generation and QA, covering STEM, programming, creative and support dialogues; Apache-2.0 licensed.

#huggingface#distillation#reasoning#llm#nlp+8
Hugging Face
AI Model·2026
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NVIDIA Nemotron-3-Embed-1B-BF16

NVIDIA

Generates 2048-d multilingual text embeddings for retrieval and semantic search, suited for RAG and dense retrieval. Pruned and distilled from the Ministral-3 family into a ~1.14B BF16 model, supports long contexts (up to 32,768 tokens) and optimized for NVIDIA GPU inference.

#nvidia#huggingface#embeddings#vllm#transformers+8
Hugging Face
AI Dataset·2026
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Claude Fable 5 Agent Traces

greghavens

Provides behavior-preserving next-step training traces from Claude Fable 5 for supervised fine-tuning and analysis of instruction-following, tool-calling, and coding agents. Runtime-normalized, independently verified, and supplied as Parquet/JSONL with 13,357 cumulative rows from 2,443 accepted trajectories.

#huggingface#anthropic#claude#ai-coding#code+6
Hugging Face
AI Model·2026
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MOSS-VL-Realtime

OpenMOSS-Team

Timestamp-aware realtime video→text model that processes incoming frames continuously, answers questions mid-stream or emits silence when evidence is insufficient, and can revise earlier outputs as new frames arrive. Built for timestamped multimodal interaction with a 256K context and an 11B-parameter backbone.

#transformers#multimodal#video#vision#huggingface+3
Hugging Face
AI Model·2026
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unsloth/inkling-GGUF

unsloth

Provides GGUF-quantized Inkling multimodal model weights for local image/audio-to-text and conversational inference. Includes quantization variants (example: 1-bit UD-IQ1_S), Apache-2.0 license, and compatibility with Unsloth Studio, vLLM and common inference stacks.

#huggingface#multimodal#image#audio#llm+2
Hugging Face
AI Dataset·2026
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SynthComp

t-tech

Evaluates retrievers and search agents on synthetic multi-hop questions that require assembling a complete set of supporting evidence. Provides English and Russian variants (395 questions each), a fixed dense index embedded with Qwen3-Embedding-8B, and BrowseComp-Plus evaluation integrations.

#qwen#evaluation#retrieval#web-search#benchmark+6
Hugging Face
AI Model·2026
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Inkling

Thinking Machines

Accepts text, image and audio inputs and generates text outputs for conversational, instruction-following and multimodal tasks; a sparse-MoE autoregressive model (975B total, 41B active) with BF16/NVFP4 support and local-deploy recipes.

#multimodal#transformers#huggingface#foundation#llm+5
Hugging Face
AI Dataset·2026
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GPT-5.6 Sol Coding & Debugging Traces

greghavens

Provides live Codex-CLI agent run traces from GPT-5.6 Sol capturing coding, debugging, security reviews, and harness/seed workflows in cumulative next-action prefixes — suitable for supervised fine-tuning and analysis of tool-using coding agents.

#codex#ai-coding#ai-agent#code#security+7
Hugging Face
AI Dataset·2026
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GLM 5.2 Agent Traces

greghavens

Behavior-preserving dataset of GLM 5.2 coding and debugging agent trajectories for supervised fine-tuning and analysis; contains 1,821 cumulative next-step rows from 207 verified trajectories with multi-turn tool use, build-test-fix loops, and runtime-normalized traces.

#huggingface#coding#code#ai-agent#agent-skills+4
Hugging Face
AI Dataset·2026
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TRuST

t-tech

Provides 324 Russian short-answer web-search tasks with gold supporting documents to evaluate fixed-index retrievers and search agents. Tasks span eight topical categories and five retrieval challenge types (multihop, structured evidence, temporal, entity disambiguation, comparative) and use a Qwen3-Embedding-8B index for evaluation.

#qwen#evaluation#embeddings#nlp#llm+4
AI Video Papers·2026
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KeyFrame-Compass: Towards Comprehensive Evaluation of Keyframe-Conditioned Video Generation

Yuqi Tang, Tengfei Liu +19

Comprehensive benchmark and automated evaluation framework for keyframe-conditioned video generation—decomposes keyframe execution into six metrics and assesses overall video quality with evidence-grounded MLLM judgments and specialized perception models.

#video#evaluation#ai-video#multimodal#vision+1
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