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
Sumedh satish gajbhiye commited on
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language: hi
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license: apache-2.0
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library_name: transformers
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tags:
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- hinglish
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language: hi
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license: apache-2.0
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library_name: transformers
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pipeline_tag: text-classification
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tags:
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- sentiment-analysis
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- hinglish
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- onnx
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# Sentiment Analyzer
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This model performs sentiment analysis on Hinglish text.
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