fineinstructions/template_instantiator

Overview

The fineinstructions/template_instantiator is a 3.2 billion parameter causal language model developed by FineInstructions. Its primary function is to take an instruction template, formatted according to the FineTemplates dataset, and a given document, then produce an instantiated instruction and its answer. The model outputs a JSON object containing the generated instruction and answer pair.

Key Capabilities

• Instruction Instantiation: Generates specific instructions from generic templates based on provided document content.
• Answer Generation: Produces an answer corresponding to the instantiated instruction, drawing information from the input document.
• Structured Output: Delivers results in a JSON format, facilitating programmatic integration and data processing.
• Excerpt Expansion: Includes a helper function to expand <excerpt> tags within the generated answer, linking back to the original document content.

Training Details

This model was trained using a synthetic dataset generated with DataDreamer 🤖💤. The training methodology focuses on creating high-quality synthetic data for instruction generation tasks.

Good For

• Synthetic Data Generation: Creating large-scale, high-quality instruction-answer pairs for training other language models.
• Automated Content Creation: Generating diverse instructions and answers for educational platforms, quizzes, or knowledge bases.
• Research in Instruction Tuning: Exploring methods for scaling instruction-following capabilities through synthetic data.