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
Download requirements.txt from Sumedhzz/Sentiment-Analyzer-Quantized: direct link, hf CLI and curl.
- Browser
- Download file 32 Bytes
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https://huggingface.co/Sumedhzz/Sentiment-Analyzer-Quantized/resolve/main/requirements.txt
- Command line
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hf download hf://Sumedhzz/Sentiment-Analyzer-Quantized/requirements.txt
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curl -L -o requirements.txt https://huggingface.co/Sumedhzz/Sentiment-Analyzer-Quantized/resolve/main/requirements.txt
32 Bytes
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| optimum | |
| onnxruntime |