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---
tags:
- finance
- stock
license: cc-by-4.0
datasets:
- SelmaNajih001/EventStockPriceVariation
language:
- en
base_model:
- allenai/longformer-base-4096
pipeline_tag: text-classification
---
# Model Card for PricePredictionForTesla
This model was created by fine-tuning a base transformer model on a dataset containing summaries of Tesla stock news along with corresponding price variations.
It is tailored specifically for predicting Tesla stock price movements after news events, providing more precise predictions than a general market model.
## Model Details
### Model Description
- **Developed by:** Salma Najih
- **Model type:** Text-Classification
- **Language(s) (NLP):** EN
- **License:** CC-BY-4.0
- **Finetuned from model:** allenai/longformer-base-4096
## Uses
The model can be used directly to estimate price movement signals from Tesla news headlines or summaries.
### Direct Use
Users can input news about Tesla, and the model will return a predicted price movement.
It provides more accurate predictions for Tesla than the general news model.
### Downstream Use
The model can be integrated into trading analysis pipelines, financial dashboards, or event-driven investment strategies, specifically for Tesla stock.
## How to Get Started with the Model
```python
from transformers import pipeline
pipe = pipeline("text-classification", model="SelmaNajih001/PricePredictionForTesla")
pipe("Tesla announces new electric vehicle")
```
Here an example of output
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