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README.md
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### 🚀 **Stage 1 Release** 🚀
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We are thrilled to introduce a specialized collection of **68 large language models (LLMs)**, meticulously designed for the accounting and finance. The FinText models have been **pre-trained** on domain-specific historical data, addressing challenges like **look-ahead bias** and **information leakage**. These models are crafted to elevate the accuracy and depth of financial research and analysis.
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💡 **Key Features:**
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- **Domain-Specific Training:** FinText utilises diverse financial datasets such as news articles, regulatory filings, IP records, corporate speeches (ECB, FED), and more.
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- **Time-Period Specific Models:** Separate models are pre-trained for each year from **2007 to 2023**, ensuring the utmost precision and historical relevance.
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### 🚀 **Stage 1 Release** 🚀
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| 22 |
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We are thrilled to introduce a specialized collection of **68 large language models (LLMs)**, meticulously designed for the accounting and finance. The FinText models have been **pre-trained** on domain-specific historical data, addressing challenges like **look-ahead bias** and **information leakage**. These models are crafted to elevate the accuracy and depth of financial research and analysis.
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💡 **Key Features:**
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- **Domain-Specific Training:** FinText utilises diverse financial datasets such as news articles, regulatory filings, IP records, corporate speeches (ECB, FED), and more.
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- **Time-Period Specific Models:** Separate models are pre-trained for each year from **2007 to 2023**, ensuring the utmost precision and historical relevance.
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