Instructions to use gsar78/HellenicSentimentAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gsar78/HellenicSentimentAI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gsar78/HellenicSentimentAI")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gsar78/HellenicSentimentAI") model = AutoModelForSequenceClassification.from_pretrained("gsar78/HellenicSentimentAI") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5e7f265707d13d53ac809b2fca335a96a4df30fb827292ae2425c0b5fd6ab5c
- Size of remote file:
- 17.1 MB
- SHA256:
- 8ad432a8ade267e0c1ecd635badacce530bb35487f87fb872fd3b9b2c79952a5
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