khazarai/Fino1-4B
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Mar 11, 2026License:apache-2.0Architecture:Transformer0.0K Open Weights Warm
khazarai/Fino1-4B is a 4 billion parameter language model, fine-tuned from Qwen3-4B, specifically designed for financial reasoning and question answering. It excels at providing structured, step-by-step reasoning for complex financial queries, leveraging a curated dataset enriched with GPT-4o-generated reasoning paths. This model is optimized for tasks such as financial report analysis and numerical reasoning over tabular financial data.
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Fino1-4B: Financial Reasoning Language Model
Fino1-4B is a specialized 4 billion parameter language model developed by khazarai, fine-tuned from the Qwen3-4B architecture. Its primary focus is on financial reasoning and question answering in English.
Key Capabilities
- Structured Financial Reasoning: Provides step-by-step, explainable answers to financial questions.
- Data-driven Insights: Adapted using LoRA fine-tuning on a dataset derived from FinQA, enhanced with GPT-4o-generated reasoning paths.
- Domain-Specific Expertise: Optimized for the finance domain, making it suitable for analyzing financial documents and data.
Good For
- Financial Report Analysis: Interpreting and extracting information from financial reports.
- Numerical Reasoning: Performing calculations and logical deductions over tabular financial data.
- Educational & Research Q&A: Generating structured answers for financial inquiries.
Limitations
- Not Financial Advice: Outputs should not be considered professional financial advice.
- Potential for Hallucinations: May misinterpret complex financial contexts or hallucinate numbers.
- Coverage: Trained on approximately 5.5K examples, which may limit its coverage for highly niche financial instruments or international standards.