Instructions to use Sumedhzz/Sentiment-Analyzer-Quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sumedhzz/Sentiment-Analyzer-Quantized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sumedhzz/Sentiment-Analyzer-Quantized")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sumedhzz/Sentiment-Analyzer-Quantized") model = AutoModelForSequenceClassification.from_pretrained("Sumedhzz/Sentiment-Analyzer-Quantized") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dac61ea1fb5b6569bbfe516e33634f78c1bddb4d3e804d37f93710b586678670
- Size of remote file:
- 279 MB
- SHA256:
- fa457743ccedd4e0aee0f67c82b2e1d7516002242a51c25be4cf164555107a32
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