mmBERT Intent Classifier (Merged for Rust)
This is a merged mmBERT model for intent classification, optimized for Rust inference using the candle framework.
Model Details
- Base Model: jhu-clsp/mmBERT-base
- Task: 14-class MMLU-Pro category classification
- Languages: Multilingual (1800+ languages)
- Training: LoRA fine-tuned then merged with base model
- Inference: Optimized for Rust candle-binding
Usage with Rust (candle-binding)
use candle_semantic_router::classifiers::lora::IntentLoRAClassifier;
let classifier = IntentLoRAClassifier::new("path/to/model", true)?;
let result = classifier.classify_intent("What is photosynthesis?")?;
println!("Intent: {}, Confidence: {:.1}%", result.intent, result.confidence * 100.0);
Classes
| ID | Category |
|---|---|
| 0 | biology |
| 1 | business |
| 2 | chemistry |
| 3 | computer science |
| 4 | economics |
| 5 | engineering |
| 6 | health |
| 7 | history |
| 8 | law |
| 9 | math |
| 10 | philosophy |
| 11 | physics |
| 12 | psychology |
| 13 | other |
Training Configuration
- LoRA Rank: 32
- LoRA Alpha: 64
- Epochs: 10
- Batch Size: 64
- Learning Rate: 2e-5
License
Apache 2.0
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Base model
jhu-clsp/mmBERT-base