FinGPT vs chat2doc.cn:怎么选?

下面把两款工具的关键信息逐项放在一起对照。 两者同属「AI 聊天」分类,属于直接竞品。

A

FinGPT

开源金融大语言模型,FinGPT官网入口网址

免费 🌍 国外 AI 聊天
B

chat2doc.cn

免费 🇨🇳 国内 AI 聊天

📊 参数逐项对照

对比项 FinGPT chat2doc.cn
价格模式 免费 免费
来源地区 🌍 国外 🇨🇳 国内
所属分类 AI 聊天 AI 聊天
用户评分 暂无评分 暂无评分
热度(浏览量) 56 166
付费说明
替代品 FinGPT 的替代品 → chat2doc.cn 的替代品 →

📖 详细介绍

FinGPT 是什么?

关于 FinGPT

@article{yang2023fingpt_open, title = {FinGPT: Open-Source Financial Large Language Models}, author = {Yang, Hongyang and Liu, Xiao-Yang and Wang, Christina Dan}, journal = {arXiv preprint arXiv:2306.06031}, year = {2023}, url = {https://arxiv.org/abs/2306.06031}, note = {First official FinGPT paper; FinLLM Workshop at IJCAI 2023} } @article{zhang2023instructfingpt, title={Instruct-FinGPT: Financial Sentiment Analysis by Instruction Tuning of General-Purpose Large Language Models}, author={Boyu Zhang and Hongyang Yang and Xiao-Yang Liu}, journal={FinLLM Symposium at IJCAI 2023}, year={2023} } @article{zhang2023fingptrag, title={Enhancing Financial Sentiment Analysis via Retrieval Augmented Large Language Models}, author={Zhang, Boyu and Yang, Hongyang and Zhou, tianyu and Babar, Ali and Liu, Xiao-Yang}, journal = {ACM International Conference on AI in Finance (ICAIF)}, year={2023} } @article{liang2024fingpt, title={FinGPT: enhancing sentiment-based stock movement prediction with dissemination-aware and context-enriched LLMs}, author={Liang, Yixuan and Liu, Yuncong and Wang, Neng and Yang, Hongyang and Zhang, Boyu and Wang, Christina Dan}, journal={AAAI 2025 Workshop GoodData}, year={2025} } @article{wang2023fingptbenchmark, title={FinGPT: Instruction Tuning Benchmark for Open-Source Large Language Models in Financial Datasets}, author={Wang, Neng and Yang, Hongyang and Wang, Christina Dan}, journal={NeurIPS Workshop on Instruction Tuning and Instruction Following}, year={2023} } @article{2023finnlp, title={Data-centric FinGPT: Democratizing Internet-scale Data for Financial Large Language Models}, author={Liu, Xiao-Yang and Wang, Guoxuan and Yang, Hongyang and Zha, Daochen}, journal={NeurIPS Workshop on Instruction Tuning and Instruction Following}, year={2023} }

demo_tasks=['Financial Sentiment Analysis','Financial Relation Extraction','Financial Headline Classification','Financial Named Entity Recognition',]demo_inputs=["Glaxo's ViiV Healthcare Signs China Manufacturing Deal With Desano","Apple Inc. Chief Executive Steve Jobs sought to soothe investor concerns about his health on Monday, saying his weight loss was caused by a hormone imbalance that is relatively simple to treat.",'gold trades in red in early trade; eyes near-term range at rs 28,300-28,600','This LOAN AND SECURITY AGREEMENT dated January 27 , 1999 , between SILICON VALLEY BANK (" Bank "), a California - chartered bank with its principal place of business at 3003 Tasman Drive , Santa Clara , California 95054 with a loan production office located at 40 William St ., Ste .',]demo_instructions=['What is the sentiment of this news? Please choose an answer from {negative/neutral/positive}.','Given phrases that describe the relationship between two words/phrases as options, extract the word/phrase pair and the corresponding lexical relationship between them from the input text. The output format should be "relation1: word1, word2; relation2: word3, word4". Options: product/material produced, manufacturer, distributed by, industry, position held, original broadcaster, owned by, founded by, distribution format, headquarters location, stock exchange, currency, parent organization, chief executive officer, director/manager, owner of, operator, member of, employer, chairperson, platform, subsidiary, legal form, publisher, developer, brand, business division, location of formation, creator.','Does the news headline talk about price going up? Please choose an answer from {Yes/No}.','Please extract entities and their types from the input sentence, entity types should be chosen from {person/organization/location}.',]

Folders and filesNameNameLast commit messageLast commit dateLatest commitHistory687 Commits687 Commits.github.github.idea.ideafigsfigsfingptfingptfinogridfinogridteststests.gitignore.gitignore.gitpod.yml.gitpod.ymlCODE_OF_CONDUCT.mdCODE_OF_CONDUCT.mdCONTRIBUTING.mdCONTRIBUTING.mdFinGPT_ Training with LoRA and Meta-Llama-3-8B.ipynbFinGPT_ Training with LoRA and Meta-Llama-3-8B.ipynbFinGPT_Inference_Llama2_13B_falcon_7B_for_Beginners.ipynbFinGPT_Inference_Llama2_13B_falcon_7B_for_Beginners.ipynbFinGPT_Training_LoRA_with_ChatGLM2_6B_for_Beginners.ipynbFinGPT_Training_LoRA_with_ChatGLM2_6B_for_Beginners.ipynbFinGPT_Training_LoRA_with_ChatGLM2_6B_for_Beginners_v2-2.ipynbFinGPT_Training_LoRA_with_ChatGLM2_6B_for_Beginners_v2-2.ipynbLICENSELICENSEMANIFEST.inMANIFEST.inREADME.mdREADME.mdUse_Cases.mdUse_Cases.mdrequirements.txtrequirements.txtsetup.pysetup.pyView all files

核心功能

  • AI CODE CREATIONGitHub CopilotWrite better code with AIGitHub Copilot appDirect agents from issue to mergeMCP RegistryNewIntegrate external tools(自动优化版)
  • GitHub CopilotWrite better code with AI(自动优化版)
  • GitHub Copilot appDirect agents from issue to merge(自动优化版)
  • MCP RegistryNewIntegrate external tools(自动优化版)
  • DEVELOPER WORKFLOWSActionsAutomate any workflowCodespacesInstant dev environmentsIssuesPlan and track workCode ReviewManage code changes(自动优化版)
  • ActionsAutomate any workflow(自动优化版)
  • CodespacesInstant dev environments(自动优化版)
  • IssuesPlan and track work(自动优化版)

chat2doc.cn 是什么?

Chat2Doc.cn是一款专注于文档交互的AI聊天工具,用户可以通过自然语言与上传的PDF、Word、Excel等文件进行对话,快速获取信息。其核心功能包括智能问答,能够理解文档内容并直接回答用户提出的问题,例如从合同或报告中提取关键数据;还支持多文档对比分析,帮助用户同时处理多个文件,找出差异或汇总要点。此外,它具备上下文记忆能力,可基于连续对话深入挖掘文档细节。这款工具适合需要频繁处理文档的办公人员、学生和研究者,尤其适用于合同审查、学术文献解读、数据分析报告梳理等场景,能显著提升信息检索和整理效率。

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