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| title: README | |
| emoji: 📚 | |
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| # Binomial Technologies | |
| **Open-source ML specialists for finance.** | |
| We build small (≤500M parameter) task-specific models for finance under Apache 2.0 — engineered for sub-second CPU inference, public eval tables, and drop-in compatibility with the pipelines quant teams actually run. | |
| ## Thesis | |
| For narrow finance tasks, small specialists beat: | |
| - **Frontier LLMs** on cost and latency by two orders of magnitude | |
| - **Dictionary methods** (Loughran-McDonald, FinBERT) on context-awareness and number of dimensions captured per article | |
| - **Closed bespoke fine-tunes** on auditability — every model card here ships with eval tables, methodology, and explicit limitations | |
| Nobody has open-sourced this stack at this fidelity. That's the gap we fill. | |
| ## The model zoo | |
| Six task-specialists named after thinkers in quantitative finance. One per quarter through 2027. | |
| | Model | Task | Status | | |
| | --------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------- | -------------------------- | | |
| | **[binomial-marks-1](https://huggingface.co/BinomialTechnologies/binomial-marks-1)** | Earnings-call NLP scoring — 23 outputs (10 topics × {mention, direction}, 3 tone) | Shipped (v1.1, April 2026) | | |
| | binomial-shannon-1 | Financial news characterizer | In progress | | |
| | binomial-godel-1 | Realized volatility forecasting | In design | | |
| | binomial-mandelbrot-1 | Market regime classification | In design | | |
| | binomial-simons-1 | Order-flow / microstructure | In design | | |
| | binomial-bachelier-1 | Vol surface dynamics | v2 cycle | | |
| All models Apache 2.0. All run under 100 ms on CPU (most under 30 ms). | |
| ## What we publish | |
| - **Weights** on this org's HF Hub | |
| - **Runtime helpers** as PyPI packages — `pip install binomial-marks` | |
| - **Source, training scripts, eval harnesses** — [github.com/Binomial-Capital-Management/binomial-ai-research](https://github.com/Binomial-Capital-Management/binomial-ai-research) | |
| - **Model cards** — full eval tables, panel comparisons, tier (1 / 2 / 3) declared upfront | |
| ## Tier system | |
| Each model card declares one of three tiers honestly: | |
| | Tier | Definition | | |
| | ----------- | -------------------------------------------------------------------------------------------------- | | |
| | **1** | Production-validated against measurable outcomes (returns, realized vol). Tradeable as a feature. | | |
| | **2** | Research preview. Eval against an LLM panel + held-out test sets. Use as input to your own models. | | |
| | **3** | Experimental. | | |
| We do not host inference. Weights are yours to deploy. | |
| ## Contact | |
| ilay@binomialtec.com |