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--- |
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language: pt |
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license: apache-2.0 |
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widget: |
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- text: "O futuro de DI caiu 20 bps nesta manhã" |
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example_title: "Example 1" |
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- text: "O Nubank decidiu cortar a faixa de preço da oferta pública inicial (IPO) após revés no humor dos mercados internacionais com as fintechs." |
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example_title: "Example 2" |
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- text: "O Ibovespa acompanha correção do mercado e fecha com alta moderada" |
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example_title: "Example 3" |
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--- |
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# FinBertPTBR : Financial Bert PT BR (Depreciated model) |
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> **Info** |
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> Newer version available on https://huggingface.co/lucas-leme/FinBERT-PT-BR |
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FinBertPTBR is a pre-trained NLP model to analyze sentiment of Brazilian Portuguese financial texts. It is built by further training the BERTimbau language model in the finance domain, using a large financial corpus and thereby fine-tuning it for financial sentiment classification. |
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## Usage |
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```python |
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from transformers import AutoTokenizer, AutoModel |
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tokenizer = AutoTokenizer.from_pretrained("turing-usp/FinBertPTBR") |
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model = AutoModel.from_pretrained("turing-usp/FinBertPTBR") |
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``` |
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## Authors |
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- [Vinicius Carmo](https://www.linkedin.com/in/vinicius-cleves/) |
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- [Julia Pocciotti](https://www.linkedin.com/in/juliapocciotti/) |
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- [Luísa Heise](https://www.linkedin.com/in/lu%C3%ADsa-mendes-heise/) |
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- [Lucas Leme](https://www.linkedin.com/in/lucas-leme-santos/) |
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