engibeer/prediction-sentiment-bist30

❤️ Prediction Sentiment Classifier

This model classifies the sentiment of stock prediction phrases from Turkish finance-related tweets.
It’s used to assign a tone (e.g., positive or negative) to the predicted movement of a stock.

🧾 Example:

"will reach 80 TL soon" → Positive
"may fall to 25 TL next week" → Negative

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🧠 Model Details

• Developed by: damlakonur
• Model type: BERT fine-tuned for sequence classification
• Language(s): Turkish
• Finetuned from: bert-base-cased
• License: MIT
• Classes: LABEL_0 = Negative, LABEL_1 = Positive

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🚀 How to Use

from transformers import pipeline

model = pipeline("text-classification", model="your-username/prediction-sentiment-bist30")

output = model("will reach 80 TL soon")
print(output)