Instructions to use nikesh66/Sentiment-Detection-using-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nikesh66/Sentiment-Detection-using-BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nikesh66/Sentiment-Detection-using-BERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nikesh66/Sentiment-Detection-using-BERT") model = AutoModelForSequenceClassification.from_pretrained("nikesh66/Sentiment-Detection-using-BERT") - Notebooks
- Google Colab
- Kaggle
Create README.md
Browse filesSentiment Analysis Model This model has total 7 labels which are as follows:
"anger"
"disgust"
"fear"
"joy"
"neutral"
"sadness"
"surprise"