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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sumedhzz/Sentiment-Analyzer-Quantized") model = AutoModelForSequenceClassification.from_pretrained("Sumedhzz/Sentiment-Analyzer-Quantized", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from Sumedhzz/Sentiment-Analyzer-Quantized: direct link, hf CLI and curl.
- Browser
- Download file 112 Bytes
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https://huggingface.co/Sumedhzz/Sentiment-Analyzer-Quantized/resolve/main/README.md
- Command line
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hf download hf://Sumedhzz/Sentiment-Analyzer-Quantized/README.md
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curl -L -o README.md https://huggingface.co/Sumedhzz/Sentiment-Analyzer-Quantized/resolve/main/README.md
112 Bytes
| library_name: transformers | |
| tags: | |
| - onnx | |
| - hinglish | |
| pipeline_tag: text-classification | |
| model_type: roberta | |