huggingface-classifier

# HuggingFace Classifier Skill ## Capabilities - Fine-tune transformer models for classification - Configure training pipelines with Trainer API - Implement inference with optimizations - Design label schemas and mappings - Set up model evaluation and metrics - Deploy models with HF Inference API ## Target Processes - intent-classification-system - entity-extraction-slot-filling ## Implementation Details ### Model Types 1. **BERT-based**: bert-base-uncased, distilbert 2. **RoBERTa-based**: roberta-base, xlm-roberta 3. **DeBERTa**: deberta-v3-base 4. **Domain-specific**: FinBERT, BioBERT ### Training Configuration - Dataset preparation - Tokenization settings - Training arguments - Evaluation metrics - Early stopping ### Configuration Options - Model selection - Number of labels - Training hyperparameters - Batch sizes - Learning rate schedules ### Best Practices - Use appropriate base model - Proper train/val/test splits - Monitor for overfitting - Evaluate on representative data ### Dependencies - transformers - datasets - accelerate