Instructions to use YarbHelp/Stock-News-Sentiment-Analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YarbHelp/Stock-News-Sentiment-Analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YarbHelp/Stock-News-Sentiment-Analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YarbHelp/Stock-News-Sentiment-Analysis") model = AutoModelForSequenceClassification.from_pretrained("YarbHelp/Stock-News-Sentiment-Analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 160aa36d7d2ecd9482ef41cce139fedce035355182d89c00d95ee873b1894917
- Size of remote file:
- 268 MB
- SHA256:
- f610a6151f3b8a88fc429e618736d750b74f2530a1c7906000127ba3c265b260
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