Quick Sentiment¶
The fastest mode for high-volume sentiment classification into positive/negative/neutral.
Usage¶
async with Sentimatrix() as sm:
result = await sm.analyze("This product is amazing!")
print(result.sentiment) # "positive"
print(result.confidence) # 0.967
When to Use¶
- High-volume filtering
- Real-time analysis
- Simple classification needs
- Resource-constrained environments
Batch Processing¶
texts = [
"Great quality!",
"Terrible experience",
"It's okay",
]
results = await sm.analyze_batch(texts)
for text, result in zip(texts, results):
print(f"{result.sentiment:>10} ({result.confidence:.0%}): {text}")
Performance¶
| Metric | Value |
|---|---|
| Latency (CPU) | ~25ms |
| Latency (GPU) | ~5ms |
| Throughput | 400+ texts/sec |