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title: Adcomment Intent Classifier | |
emoji: π | |
colorFrom: blue | |
colorTo: gray | |
sdk: gradio | |
sdk_version: 5.34.1 | |
app_file: app.py | |
pinned: false | |
license: mit | |
# Ad Comments Intent Classifier | |
This Space provides an interface for classifying the intent of comments related to advertisements using the `YosefA/adfluence-intent-model`. | |
## Features | |
- π― **Intent Classification**: Analyze comment text to determine the underlying intent | |
- π **Confidence Scores**: Get probability scores for each predicted label | |
- π‘ **Easy to Use**: Simple interface with example comments provided | |
- β‘ **Fast Inference**: Optimized for quick classification results | |
## How to Use | |
1. Enter your comment text in the input box | |
2. Click "π Classify Intent" or press Enter | |
3. View the classification results with confidence scores | |
## Model Information | |
This app uses the `YosefA/adfluence-intent-model` from Hugging Face, which is trained to classify the intent of comments in advertising contexts. | |
## Examples | |
Try these example comments to see how the classifier works: | |
- "This product looks amazing! Where can I buy it?" | |
- "This is clearly a scam, don't trust it." | |
- "I love this brand, they make quality products." | |
- "The price seems too high for what you get." | |
- "Has anyone tried this? I'm curious about reviews." |