706 Downloads Updated 3 months ago
🔗 Model Link: https://huggingface.co/tarun7r/Finance-Llama-8B
🔗 Quantized Model: https://huggingface.co/tarun7r/Finance-Llama-8B-q4_k_m-GGUF
This model is a fine-tuned version of unsloth/Meta-Llama-3.1-8B on the Josephgflowers/Finance-Instruct-500k dataset. It’s designed for financial tasks, reasoning, and multi-turn conversations.
Tarun Sai Goddu - Data Scientist at Jio Platforms Ltd (2+ years experience) | IIT Bombay
Expertise: AI Agents • RAG Pipelines • Computer Vision • NLP • Speech Domain
Actively seeking opportunities as an ML Engineer II / Data Scientist II where I can contribute to building scalable, production-ready AI/ML systems.
Reach me here:
- LinkedIn: linkedin.com/in/tarunsaigoddu | Email: tarunsaiaa@gmail.com
- GitHub: github.com/tarun7r
Overview Finance-Instruct-500k is a comprehensive and meticulously curated dataset designed to train advanced language models for financial tasks, reasoning, and multi-turn conversations. Combining data from numerous high-quality financial datasets, this corpus provides over 500,000 entries, offering unparalleled depth and versatility for finance-related instruction tuning and fine-tuning.
The dataset includes content tailored for financial reasoning, question answering, entity recognition, sentiment analysis, address parsing, and multilingual natural language processing (NLP). Its diverse and deduplicated entries make it suitable for a wide range of financial AI applications, including domain-specific assistants, conversational agents, and information extraction systems.
Key Features of the Dataset
Extensive Coverage: Over 500,000 entries spanning financial QA, reasoning, sentiment analysis, topic classification, multilingual NER, and conversational AI.🌍
Multi-Turn Conversations: Rich dialogues emphasizing contextual understanding & reasoning.🗣️
Diverse Data Sources: Includes entries from Cinder, Sujet-Finance-Instruct-177k, Phinance Dataset, BAAI/IndustryInstruction_Finance-Economics, Josephgflowers/Financial-NER-NLP, and many other high-quality datasets. 📖
Citation 📌
@misc{tarun7r/Finance-Llama-8B,
author = {[tarun7r]},
title = {tarun7r/Finance-Llama-8B: A Llama 3.1 8B Model Fine-tuned on Josephgflowers/Finance-Instruct-500k},
year = {2025},
publisher = {Hugging Face},
journal = {Hugging Face Model Hub},
howpublished = {\url{https://huggingface.co/tarun7r/Finance-Llama-8B}}
}