This is a perfect first project to show the power of our Hugging Face Hub. We will use a pre-trained AI model to instantly determine if a sentence is positive or negative.
Step 1: Installation
pip install transformers(You may also need pip install torch if you don’t have it).
Step 2: The Code
from transformers import pipeline
# 1. Load the pipeline (This downloads a pre-trained model for you)
classifier = pipeline("sentiment-analysis")
# 2. Define your text
text = "I love this product! It's the best thing I've ever bought."
# 3. Classify!
result = classifier(text)
# 4. Print the result
print(result)Step 3: Understanding the Output
The output will look like this: [{'label': 'POSITIVE', 'score': 0.999874...}]
The model is 99.98% sure that this text is POSITIVE.
Let’s try a negative one:
result = classifier("This movie was terrible. I fell asleep.")
print(result)
# Output: [{'label': 'NEGATIVE', 'score': 0.9997...}]How to Use This
You can now build powerful apps!
- Loop through a CSV of customer reviews to find all the unhappy ones.
- Analyze live tweets about your brand.
- Auto-sort feedback emails.
