Instructions to use Roy229/nml7324-sentiment-analyzer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Roy229/nml7324-sentiment-analyzer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Roy229/nml7324-sentiment-analyzer")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Roy229/nml7324-sentiment-analyzer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Sentiment Analyzer
A production model that classifies customer feedback into positive, negative and neutral sentiment across multiple support channels. It powers the Net-Promoter-Score survey pipeline and the customer-success triage queue, processing roughly two million messages per day with a target latency under 80 milliseconds per prediction.
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