AI Model2026
Unified 4B vision-language model for document understanding that converts images or text into template-driven structured JSON or clean Markdown. Key features: multimodal inputs (image+text), template-based extraction, reasoning vs non-reasoning modes, and vLLM/OpenAI-compatible deployment for OCR, invoice/forms extraction, and RAG preprocessing.
AI Dataset2026
Provides ~85K contrastive visual question–answer pairs where each example contains an anchor and a matched counterpart (image, question, answer). Pairs span General, Reasoning, Math, Graph/Chart and OCR categories to help train and evaluate fine‑grained, faithful visual reasoning in VLMs.
AI Model2026
An uncensored, fine-tuned and GGUF-quantized variant of Qwen3.6-27B tailored for long-context, coding, vision and creative-writing use. Offers multiple NEO-CODE Di-Matrix quants (IQ2/IQ4/Q6/Q8), mmproj vision support and recommended inference settings for local servers.
AI Model2026
Multilingual 2B speech–language model for ASR and bidirectional speech translation (EN, FR, DE, ES, PT, JA), providing punctuation/truecasing, keyword biasing, and a dual-head CTC encoder to boost transcription accuracy.
AI Dataset2026
Early-preview (≈1.2k rows) dataset of agentic coding prompts and unedited model responses generated by DeepSeek‑V4‑Pro, covering real-world programming tasks across many languages. Intended for research, filtering, and model evaluation rather than production training without review.
AI Model2026
Generates high-fidelity 3D assets from a single image by back-projecting pixel-aligned features into 3D, preserving fine geometry and PBR textures; includes inference code and a Hugging Face demo—best suited for single-view object reconstruction.
AI Dataset2026
Provides the dataset and accompanying technical report for a DeepSeek project that interleaves spatial markers (points and boxes) into multimodal LLM reasoning. Includes a public subset of data and benchmarks under an MIT license; model weights are not included.
AI Model2026
Draft model for speculative decoding that uses a lightweight block-diffusion drafter to propose multiple tokens in parallel; designed to pair with google/gemma-4-31B-it and accelerate autoregressive text generation (official benchmarks report up to ~5.8× throughput).
AI Model2026
DavidAU/Qwen3.6-40B-Claude-4.6-Opus-Deckard-Heretic-Uncensored-Thinking-NEO-CODE-Di-IMatrix-MAX-GGUF
A 40B GGUF-quantized Qwen3.6 variant fine-tuned with Claude 4.6 Opus and Deckard/Heretic datasets for multimodal image-text-to-text tasks. Offers 256K context, custom NEO-CODE Di-IMatrix quants for long conversations and coding, optimized for local inference and creative/coding use cases; safety alignment removed.
AI Dataset2026
Provides 545,431 math problems with model-generated solution traces (chain-of-thought and Python tool-integrated reasoning) verified against reference answers for training and evaluating LLM mathematical reasoning. Parquet-format dataset; DeepSeek‑V4‑Pro generated traces and mixed CC BY / CC BY‑SA licensing.
AI Dataset2026
Collects ML Intern coding-agent session traces as Claude‑Code‑style JSONL event streams for viewing with the Hugging Face Agent Trace Viewer. Each file is one session (messages, tool calls, outputs, timestamps); automated scrubbing is applied but no comprehensive human redaction—treat as potentially sensitive.
AI Dataset2026
Instruction‑tuning dataset of 8,706 Claude Opus 4.6/4.7–generated examples where each assistant turn begins with a synthetic <think> block to emulate chain‑of‑thought. Provided as four splits (full/instruct/roleplay/code), ~17M tokens total, Apache‑2.0, not manually reviewed.