This is a fine-tuned Named Entity Recognition (NER) model that extracts stock prediction phrases from Turkish financial tweets. These prediction phrases are later passed into a sentiment classifier for further analysis.

🧾 Example predictions:

"will reach 70 TL"
"to moon soon"
"drop to 50 in 2 weeks"

🧠 Model Details

Developed by: damlakonur
Model type: BERT fine-tuned for token-classification
Language(s): Turkish
Finetuned from: bert-base-cased
Entity type: Tahmin (prediction phrase)
License: MIT

🚀 How to Use

python

from transformers import pipeline

model = pipeline(
    "token-classification",
    model="your-username/prediction-text-ner-bist30",
    aggregation_strategy="simple"
)

model("EREGL will reach 45 TL in June.")

engibeer/prediction-text-ner-bist30

🧠 Prediction Phrase Extractor (NER)

🧠 Model Details

🚀 How to Use

engibeer/
prediction-text-ner-bist30