README.md

metadata

tags:
  - sentiment-analysis
  - transformers
  - text-classification
license: apache-2.0
datasets:
  - imdb
language:
  - en

Simple Sentiment Analyzer

🚀 This is a sentiment analysis model trained to classify text as Positive or Negative.

Model Details

• Architecture: DistilBERT (fine-tuned for sentiment classification)
• Framework: 🤗 Transformers
• Files included:
  • config.json
  • model.safetensors
  • tokenizer.json
  • tokenizer_config.json
  • special_tokens_map.json
  • vocab.txt

Usage

from transformers import pipeline

classifier = pipeline("sentiment-analysis", model="Rugs25/simple-sentiment-analyzer")

print(classifier("I love Hugging Face!"))  # → POSITIVE
print(classifier("This is terrible."))     # → NEGATIVE