Instructions to use jzuluagav97/NPL-CX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jzuluagav97/NPL-CX with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jzuluagav97/NPL-CX")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jzuluagav97/NPL-CX") model = AutoModelForSequenceClassification.from_pretrained("jzuluagav97/NPL-CX") - Notebooks
- Google Colab
- Kaggle
Sentiment Analysis Model (SP)
Model Performance
- Accuracy in 3 categories: 67.59%
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