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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d25b2b481556c0a9c9d4ed864f874028a20f64f928f74f2604e976ff86c3df6a
- Size of remote file:
- 329 MB
- SHA256:
- 9bb17cf64101e499d1be46a0059df4cc745531ba76eab7aca9d08e870db36318
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