socratesft/socrates-llama3-8b-sft
socratesft/socrates-llama3-8b-sft is an 8 billion parameter Llama 3-based model developed by socratesft, specifically fine-tuned using Supervised Fine-Tuning (SFT) on survey response data. This model excels at simulating survey respondents and generating precise, demographically-aligned answers to survey questions. It is designed for tasks requiring nuanced, persona-based text generation within a survey context, leveraging an 8192-token context length.
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Model Overview
socratesft/socrates-llama3-8b-sft is an 8 billion parameter language model built upon the Meta-Llama-3-8B-Instruct base model. It has undergone Supervised Fine-Tuning (SFT) using the specialized socratesft/SocSci210 dataset, which focuses on participant_mapping for survey responses.
Key Capabilities
- Simulating Survey Respondents: The model is specifically trained to act as a survey respondent, adhering to given demographic profiles and answering questions precisely as that persona would.
- Precise Response Generation: It is designed to follow strict response instructions, such as returning only a numerical choice without additional commentary, making it suitable for structured data collection or analysis.
- Contextual Understanding: Leveraging the Llama 3 architecture, it can process detailed demographic profiles and complex survey questions within an 8192-token context window to generate relevant answers.
Ideal Use Cases
- Social Science Research: Generating synthetic survey data based on specific demographic parameters for research and analysis.
- Market Research Simulation: Simulating target audience responses to product or service questions.
- Persona-Based Content Generation: Creating text that accurately reflects a defined persona's perspective in a question-and-answer format.
This model is licensed under the Meta Llama 3 Community License Agreement.