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
- Xet hash:
- 2f3451f46f7de1426d5d1d8f42ae8923c3447b3675bdaaa0ff3252df7e5b2422
- Size of remote file:
- 595 MB
- SHA256:
- 68656ac2c3b1e9bca1d4682854224fb747726a0f07bf1cf8eb19c059e39b4dbb
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