README.md

metadata

title: LLM & Arithmetic
emoji: 🔢
colorFrom: blue
colorTo: green
sdk: docker
pinned: false
short_description: Explore LLM arithmetic and next-prime datasets.

LLM & Arithmetic

Explore LLM arithmetic and next-prime experiments across raw, prompted, and tool modes.

Streamlit explorer for two public Hugging Face datasets:

• hoololi/llm-calculations
• hoololi/llm-next-prime

The app compares how LLMs behave on arithmetic-like tasks across three modes:

• raw: direct answer;
• prompted: task-oriented system prompt;
• tool: external deterministic tool available to the model.

Features

• top-level tabs for Calculations and Next Prime;
• nested Statistics and Detailed results views for each dataset;
• model comparison across raw, prompted, and tool modes;
• charts for accuracy, latency, cost, tokens, and category/magnitude breakdowns;
• tool-pipeline summaries where relevant;
• side-by-side inspection of two model × mode results for the same task;
• quick filters for wrong answers, run failures, tool issues, long answers, slowest answers, fastest answers, and high-cost rows;
• OpenRouter model metadata snapshot display when available.

The app loads the datasets directly from Hugging Face and is containerized with Docker.

To refresh OpenRouter metadata, update model_families.json if needed and run:

python fetch_openrouter_model_info.py