FIN-GPT.AI

Paid

FinGPT: Open-source financial LLMs with real-time data and low-cost fine-tuning

#Financial AI#Open-source#Large Language Model#LLM#Real-time data pipeline#Sentiment Analysis#Time series prediction#Fine-tuning methods#Robo-advising#Trading applications

Type

Saas

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About FIN-GPT.AI

FinGPT is an open-source financial large language model (LLM) platform that democratizes financial AI with zero-cost training, a modular real-time data pipeline from 117+ sources, and efficient fine-tuning methods (LoRA/QLoRA/RLSP). It offers pre-trained FinGPT models (v3.3 for robo-advising, v3.2 for sentiment), the FinGPT-Forecaster (THG 7B/13B) for time series prediction, and reproducible deployment via Docker, Hugging Face, and cloud. Benchmarks show FinGPT surpasses GPT-4 in robo-advising and FinBERT in sentiment analysis, enabling applications in trading, risk, and advisory.

Key Features

Open-source, MIT-licensed financial LLM platform

Zero-cost training paradigm with massive real-time data

Modular pipeline spanning 117+ data sources (news, social, filings, markets)

Lightweight adaptation via LoRA and QLoRA; RLSP for alignment

Pre-trained FinGPT models: v3.3 (robo-advising) and v3.2 (sentiment)

FinGPT-Forecaster THG (7B/13B) for time series prediction

FinGPT-Bench for finance-specific evaluation (sentiment, NER, RE, QA)

Multi-granularity processing at ticker, industry, market, and global levels

One-click deployment via Docker, Kubernetes, Hugging Face, and Colab

Benchmark-leading results vs. GPT-4 (robo-advising) and FinBERT (sentiment)

Best For

Quant researcher: Backtest and evaluate LLM-driven trading signals using FinGPT sentiment and forecasting outputs.Portfolio manager: Enhance asset allocation and rebalancing with robo-advising models fine-tuned on market regimes.Retail trader: Gauge real-time market sentiment from news and social feeds to inform trade timing.Risk manager: Monitor entity- and sector-level risks via NER/relation extraction on filings and news.Fintech startup: Embed a compliant, cost-efficient financial copilot using LoRA/QLoRA-adapted FinGPT models.Data engineer: Automate ingestion and cleaning of multi-source financial data with the modular pipeline.Research analyst: Summarize earnings calls and extract guidance signals for coverage reports.Compliance team: Scan disclosures and regulatory updates (EDGAR) for material changes and red flags.Product manager: Stand up demos on Hugging Face and scale to Docker/Kubernetes for production.Academic/Student: Reproduce benchmarks and explore instruction tuning and RLHF for finance tasks.

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