chenyicheng commited on
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93d043d
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1 Parent(s): 8e0f4df

update app

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Files changed (1) hide show
  1. app.py +1 -1
app.py CHANGED
@@ -89,7 +89,7 @@ PRESETS = {
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  "benchmark": {
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  "name": "OpenFinData",
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  "description": (
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- "The OpenFinData dataset comprises six modules, each encompassing multiple task dimensions to address diverse evaluation requirements in the financial sector: Financial Knowledge, Financial Discrimination, Financial Computation, Financial Analysis, Financial Interpretation, and Financial Compliance. Examples: [{\“question\”: \"You are a financial data review assistant. Identify which data point contains an obvious error. Provide the correct option. \nEuropean bond yields closed higher across the board. UK 10-year government bond yields rose 6.1 basis points to 4.328%, French 10-year yields gained 7 basis points to 3.298%, German 10-year yields increased 7.1 basis points to 2.714%, and Italian 10-year yields climbed 6.2 basis points to 4.567%. and the Spanish 10-year government bond yield rose 6.8 basis points to 3.758%.\nA. No obvious errors in the data\nB. UK 10-year government bond yield rose 6.1 basis points to 4.328%\nC. French 10-year government bond yield rose 7 basis points to 3.298%\nD. German 10-year government bond yields rose 7.1 basis points to 2.714%, Italian 10-year government bond yields rose 6.2 basis points to 4.567%“, ”answer“: ‘A’, {\”question\“: ”You are an entity recognition assistant. Please list the stock market concept sectors mentioned in the following content. Recently, autonomous driving concept stocks have surged strongly, with continuous inflow of incremental capital injecting new momentum into the automotive sector. Meanwhile, the implementation of relevant regulations has allowed Level 3 and Level 4 autonomous vehicles to be approved for road use, which is expected to significantly promote the development of domestic autonomous driving technology.“, answer: ”Autonomous Driving"}]."
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  ),
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  },
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  },
 
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  "benchmark": {
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  "name": "OpenFinData",
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  "description": (
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+ "The OpenFinData dataset comprises six modules, each encompassing multiple task dimensions to address diverse evaluation requirements in the financial sector: Financial Knowledge, Financial Discrimination, Financial Computation, Financial Analysis, Financial Interpretation, and Financial Compliance. Examples: [{\“question\”: \"You are a financial data review assistant. Identify which data point contains an obvious error. Provide the correct option. \nEuropean bond yields closed higher across the board. UK 10-year government bond yields rose 6.1 basis points to 4.328%, French 10-year yields gained 7 basis points to 3.298%, German 10-year yields increased 7.1 basis points to 2.714%, and Italian 10-year yields climbed 6.2 basis points to 4.567%. and the Spanish 10-year government bond yield rose 6.8 basis points to 3.758%.\nA. No obvious errors in the data\nB. UK 10-year government bond yield rose 6.1 basis points to 4.328%\nC. French 10-year government bond yield rose 7 basis points to 3.298%\nD. German 10-year government bond yields rose 7.1 basis points to 2.714%, Italian 10-year government bond yields rose 6.2 basis points to 4.567%“, ”answer“: ‘A’, {\”question\“: ”You are an entity recognition assistant. Please list the stock market concept sectors mentioned in the following content. Recently, autonomous driving concept stocks have surged strongly, with continuous inflow of incremental capital injecting new momentum into the automotive sector. Meanwhile, the implementation of relevant regulations has allowed Level 3 and Level 4 autonomous vehicles to be approved for road use, which is expected to significantly promote the development of domestic autonomous driving technology.“, \"answer\": \”Autonomous Driving\"}]."
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  ),
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  },
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  },