# Financial Q&A

A financial domain-specific model fine-tuned from Llama 3.1 8B, excelling in financial reasoning, Q&A, and multi-turn dialogues

Fino1-8B is a fine-tuned version based on Llama 3.1 8B Instruct, focusing on improving performance in financial reasoning tasks.

This is a financial domain language model fine-tuned based on the DeepSeek-R1-Distill-Llama-8B model, optimized using LoRA technology, suitable for financial Q&A and instruction tasks.

WiroAI-Finance-Gemma-9B is a financial domain language model based on the Google Gemma architecture. It has been fine-tuned with high-quality financial data and is good at handling financial-related issues.

A financial domain-specific language model fine-tuned based on LLAMA 3 8B, focusing on financial text analysis tasks

A financial domain-specific chat model developed based on LLaMA-2-Chat-7B, optimized for domain knowledge through reading comprehension methods

ZhiLu is a financial large language model developed based on Chinese Alpaca2-13B, achieving capability leaps through massive incremental pre-training with Chinese and English corpora and high-quality instruction data alignment, with a focus on enhancing performance in the financial domain.

A RoBERTa-base model fine-tuned for financial domain Q&A tasks, specifically designed for customized Q&A systems in banking, finance, and insurance sectors.