Instructions to use SelmaNajih001/SentimentBasedOnPriceVariation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SelmaNajih001/SentimentBasedOnPriceVariation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SelmaNajih001/SentimentBasedOnPriceVariation")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SelmaNajih001/SentimentBasedOnPriceVariation") model = AutoModelForSequenceClassification.from_pretrained("SelmaNajih001/SentimentBasedOnPriceVariation") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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## How to Get Started with the Model
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Use the code below to get started with the model.
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from transformers import pipeline
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pipe = pipeline("text-classification", model="SelmaNajih001/SentimentBasedOnPriceVariation")
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## How to Get Started with the Model
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Use the code below to get started with the model.
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```python
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from transformers import pipeline
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pipe = pipeline("text-classification", model="SelmaNajih001/SentimentBasedOnPriceVariation")
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