Example Use Case Tutorials

These end-to-end examples serve as tutorials for the usage of RapidFire AI’s API. They use publicly available datasets, models, and code.

For RAG and Context Engineering

We have one use case example each for an all-local model, all-OpenAI, and a hybrid workflow: FiQA RAG Q&A chatbot, SciFact RAG for scientific claim verification, and GSM8K few-shot/context engineering for math reasoning, respectively. This set will expand over time to more examples based on community inputs.

• FiQA: RAG for Financial Opinion Q&A Chatbot
  • Task, Dataset, and Prompt
  • Model, RAG Components, and Configuration Knobs
• GSM8K: Context Engineering for Math Reasoning
  • Task, Dataset, and Prompt
  • Model, Few-Shot Selection, and Configuration Knobs
• SciFact: RAG for Scientific Claim Verification
  • Task, Dataset, and Prompt
  • Model, RAG Components, and Configuration Knobs

For Fine-Tuning and Post-Training

We have one example for each supported control flow from HuggingFace TRL: SFT, DPO, and GRPO. This set will expand over time to more examples based on community inputs.

You can also check out RapidFire AI on Google Colab instead of your own machine; it showcases a simplified SFT use case.

• SFT for Q&A Chatbot
  • Task, Dataset, and Prompt
  • Model, Adapter, and Trainer Knobs
• DPO for Alignment
  • Task, Dataset, and Prompt
  • Model, Adapter, and Trainer Knobs
• GRPO for Math Reasoning
  • Task, Dataset, and Prompt
  • Model, Adapter, and Trainer Knobs