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| title: ThingsAI | |
| sdk: static | |
| emoji: 📚 | |
| colorFrom: indigo | |
| colorTo: blue | |
| type: org | |
| tags: | |
| - slm | |
| - llm | |
| - pytorch | |
| - amdl | |
| - math | |
| - code | |
| # Welcome to ThingsAI. Building highly efficient, logic-driven Small Language Models that run anywhere. | |
| ## Our Models | |
| * **Quark-135M** | |
| A lightweight bilingual (Italian + English) language model with 135M parameters. Features GQA, SwiGLU, RMSNorm, and RoPE. Trained on 50B+ tokens of curated data. | |
| * **Quark-270M** | |
| Our scaled small model featuring 270M parameters, 32 layers, 768 hidden dimensions, and a 65K vocabulary. Designed for extended bilingual capabilities. | |
| * **Quark-Math-Code (72M)** | |
| Our ultra-compact, deep-thin architecture (72M parameters, 14 layers, 65K vocabulary) engineered specifically for STEM, coding, and mathematical reasoning. Actively pre-training on a 5B token target with a hardened Chain-of-Thought (CoT), OpenWebMath, and pure-code mix. | |
| * **Quark-Mod** | |
| A multi-label moderation model covering 9 categories for safe AI deployment: toxic, severe_toxic, obscene, threat, insult, identity_hate, cyberbullying, hate_speech, offensive. | |
| ## What We Focus On | |
| * **Hyper-Efficient Architectures:** Mastering the sub-1B parameter space using GQA, Grouped-Query Attention, and deep-thin layer scaling. | |
| * **Embedded Chain-of-Thought (CoT):** Hardcoding step-by-step reasoning tokens into the pre-training phase of tiny models to punch far above their weight class in logic benchmarks. | |
| * **Bilingual & Specialty Data:** Multi-source streaming pipelines fusing Italian, English, high-density mathematics, and code. | |
| * **Open-Source & Real-World Deployable:** Everything from weights to datasets is open. Tailored to achieve massive throughput on consumer GPUs and edge hardware. | |
| ## Resources | |
| * **Quark-135M-Bilingual:** Our flagship general-purpose bilingual model. | |
| * **Quark-Mod:** Multi-label content moderation for production pipelines. | |
| * **HuggingFace Community:** All our released models, tokenizers, and custom datasets. | |
| * **GitHub Open Source:** Training scripts, custom multi-source streaming iterators, and deployment tools. |