/huggingface-classifier

name: huggingface-classifier
description: Hugging Face transformer model fine-tuning and inference for intent classification
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graph:
  domains: [domain:software-engineering]
  specializations: [specialization:ai-agents-conversational]
  skillAreas: [skill-area:natural-language-processing, skill-area:ml-fine-tuning]
  roles: [role:ml-engineer, role:backend-engineer]
  workflows: [workflow:ml-model-lifecycle, workflow:feature-development]

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