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:
- 05e0eee3eb15165e9c3a18f4d7b06e1a4d5fc704091f149e70e6d94abdfeebf6
- Size of remote file:
- 16.8 MB
- SHA256:
- ba7ba696dcec1db50526d3643ab6c496f28977ec60217f2a3d1388d6250cd0a6
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