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:
- 0b6af6a3f22e61551ac960015b0c0a0c358cf28dacd536faae3564dbce45df69
- Size of remote file:
- 3.07 kB
- SHA256:
- 00d565b6a8713b3586de49f9e5ceafbb367cbda27c3518f4e9f54349cb59bef4
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