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Rustamshry/Personal-Finance-R2-GGUF

sourceHugging Faceapache-2.0updated 6mo agoView on Hugging Face
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GGUF version of https://huggingface.co/khazarai/Personal-Finance-R2

This model is fine-tuned for instruction-following in the domain of personal finance, with a focus on:

  • —Budgeting advice
  • —Investment strategies
  • —Credit management
  • —Retirement planning
  • —Insurance and financial planning concepts
  • —Personalized financial reasoning

Model Description

  • —License: MIT
  • —Finetuned from model: unsloth/Qwen3-1.7B
  • —Dataset: The model was fine-tuned on the Kuvera-PersonalFinance-V2.1, curated and published by Akhil-Theerthala.

Model Capabilities

  • —Understands and provides contextual financial advice based on user queries.
  • —Responds in a chat-like conversational format.
  • —Trained to follow multi-turn instructions and deliver clear, structured, and accurate financial reasoning.
  • —Generalizes well to novel personal finance questions and explanations.

Uses

Direct Use

  • —Chatbots for personal finance
  • —Educational assistants for financial literacy
  • —Decision support for simple financial planning
  • —Interactive personal finance Q&A systems

Bias, Risks, and Limitations

  • —Not a substitute for licensed financial advisors.
  • —The model's advice is based on training data and may not reflect region-specific laws, regulations, or financial products.
  • —May occasionally hallucinate or give generic responses in ambiguous scenarios.
  • —Assumes user input is well-formed and relevant to personal finance.

Training Data

  • —Dataset Overview: Kuvera-PersonalFinance-V2.1 is a collection of high-quality instruction-response pairs focused on personal finance topics. It covers a wide range of subjects including budgeting, saving, investing, credit management, retirement planning, insurance, and financial literacy.
  • —Data Format: The dataset consists of conversational-style prompts paired with detailed and well-structured responses. It is formatted to enable instruction-following language models to understand and generate coherent financial advice and reasoning.