Instructions to use divyansh126/SentimentAnalysisBert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use divyansh126/SentimentAnalysisBert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="divyansh126/SentimentAnalysisBert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("divyansh126/SentimentAnalysisBert") model = AutoModelForSequenceClassification.from_pretrained("divyansh126/SentimentAnalysisBert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9214147e173dfeba632f2dba436bab677b7373c8dd8dfce594c1adbffb11a648
- Size of remote file:
- 438 MB
- SHA256:
- 59649ede8c73dde8e87e0154e16fb6f3c6a4ad1700ac0369a34670fe35d87f3c
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