DistilBERT Sentiment Analysis
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Platform: Replicate
Sentiment AnalysisText ClassificationBatch Processing
105 runs
T4
License Check Required🚀Function Overview
A DistilBERT model fine-tuned for sentiment analysis that processes batches of text inputs to predict sentiment labels and confidence scores.
Key Features
- Fine-tuned BERT architecture for efficient text classification
- Batch processing of multiple texts in a single API call
- Outputs predicted sentiment labels (0=negative, 1=positive) with confidence scores
- Optimized for performance and reduced compute costs
Use Cases
- •Sentiment analysis of customer reviews
- •Social media emotion monitoring
- •Product feedback classification
- •Batch-processing text data for research
⚙️Input Parameters
texts
stringA JSON-formatted list of texts for sentiment analysis
💡Usage Examples
Example 1
Input Parameters
{
"texts": "[\"I will miss apple\",\"I love apple\"]"
}Output Results
{
"confidences": [
0.9994000196456909,
0.9998000264167786
],
"predicted_labels": [
0,
1
]
}
Quick Actions
Technical Specifications
- Hardware Type
- T4
- Run Count
- 105
- Commercial Use
- Unknown/Restricted
- Platform
- Replicate