Update README.md

README.md

@@ -29,3 +29,44 @@ configs:
 [zeroshot/twitter-financial-news-sentiment](https://huggingface.co/datasets/zeroshot/twitter-financial-news-sentiment) prepared for LLM fine-tuning
 by adding an `instruction` column and mapping the label from numeric to string (`{0:"negative", 1:'positive', 2:'neutral'}`).
 
+[Source](https://github.com/AI4Finance-Foundation/FinGPT/blob/master/fingpt/FinGPT-v3/data/making_data.ipynb)
+```python
+from datasets import load_dataset
+import datasets
+
+from huggingface_hub import notebook_login
+notebook_login()
+
+ds = load_dataset('zeroshot/twitter-financial-news-sentiment')
+
+num_to_label = {
+    0: 'negative',
+    1: 'positive',
+    2: 'neutral',
+}
+
+instruction = 'What is the sentiment of this tweet? Please choose an answer from {negative/neutral/positive}.'
+
+# Training split
+
+ds_train = ds['train']
+ds_train = ds_train.to_pandas()
+ds_train['label'] = ds_train['label'].apply(num_to_label.get)
+ds_train['instruction'] = instruction
+ds_train.columns = ['input', 'output', 'instruction']
+ds_train = datasets.Dataset.from_pandas(ds_train)
+
+ds_train.push_to_hub("twitter-financial-news-sentiment")
+
+# Validation split
+
+ds_valid = ds['validation']
+ds_valid = ds_valid.to_pandas()
+ds_valid['label'] = ds_valid['label'].apply(num_to_label.get)
+ds_valid['instruction'] = instruction
+ds_valid.columns = ['input', 'output', 'instruction']
+ds_valid = datasets.Dataset.from_pandas(ds_valid, split='validation')
+
+ds_valid.push_to_hub("twitter-financial-news-sentiment", split='validation')
+```
+