soleimanian
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financial-roberta-large-sentiment

Text Classification

Financial Statements

Earnings Call Transcripts

Corporate governance

Inference Endpoints

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soleimanian commited on May 16, 2022

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@@ -18,6 +18,7 @@ license: apache-2.0
 </ul>
 <p>Financial-RoBERTa is built by further training and fine-tuning the RoBERTa Large language model using a large corpus created from 10k, 10Q, 8K, Earnings Call Transcripts, CSR Reports, ESG News, and Financial News text.</p>
 <p>The model will give softmax outputs for three labels: <b>Positive</b>, <b>Negative</b> or <b>Neutral</b>.</p>
 <p>The easiest way to use the model for single predictions is Hugging Face's sentiment analysis pipeline, which only needs a couple lines of code as shown in the following example:</p>
 <pre>
   <code>

 </ul>
 <p>Financial-RoBERTa is built by further training and fine-tuning the RoBERTa Large language model using a large corpus created from 10k, 10Q, 8K, Earnings Call Transcripts, CSR Reports, ESG News, and Financial News text.</p>
 <p>The model will give softmax outputs for three labels: <b>Positive</b>, <b>Negative</b> or <b>Neutral</b>.</p>
+<p><b>How to perform sentiment analysis:</b></p>
 <p>The easiest way to use the model for single predictions is Hugging Face's sentiment analysis pipeline, which only needs a couple lines of code as shown in the following example:</p>
 <pre>
   <code>