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| title: ThingAI | |
| type: org | |
| tags: | |
| - slm | |
| - llm | |
| - pytorch | |
| - bash | |
| - shell | |
| - code | |
| - tokenizer | |
| - rust | |
| # ThingsAI | |
| Building efficient, specialist Small Language Models that run on consumer hardware. Zero telemetry. Open weights. Everything from tokenizer to training script is public. | |
| ## Models | |
| * **Dwarf-15M** | |
| A 15.54M parameter shell/bash specialist. 12 layers, d_model=320, GQA 5Q/1KV, SwiGLU, RMSNorm, RoPE. Custom 8202-token vocabulary via DwarfGoToken. 1390:1 token-to-parameter ratio across 11 datasets spanning raw shell, Python, C, instruction pairs, and English web text. Target use case: CLI tool that translates natural language into bash commands with user review before execution. | |
| * **Quark-270M** | |
| Our largest model. 252M effective parameters, 32 layers, d_model=768, GQA 12Q/4KV, 65K bilingual vocabulary (Italian + English). Trained on curated multilingual data. Available as Base and Instruct variants. | |
| * **Quark-135M** | |
| Bilingual (Italian + English) general-purpose model. 135M parameters, 30 layers, 9 attention heads (3 KV, GQA), SwiGLU, RMSNorm, RoPE θ=10k. Trained on 15B+ tokens. Published benchmarks: HellaSwag 31.37%, ARC-Easy 41.46%, PIQA 61.26%. | |
| ## Links | |
| * Models and tokenizers: [HuggingFace](https://huggingface.co/ThingAI) | |
| * Script & Tool: [GitHub](https://github.com/overcastlab) | |
| * Website: [things-ai.org](https://things-ai.org) | |
| * GoToken: [crates.io](https://crates.io/crates/gotoken) · [PyPI](https://pypi.org/project/gotoken/) |