# Huggingface Classifier

> Hugging Face transformer model fine-tuning and inference for intent classification

- Skill: `a5c-ai/huggingface-classifier` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add a5c-ai/huggingface-classifier`
- Raw SKILL.md: https://api.skillmd.com/api/skills/a5c-ai/huggingface-classifier/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: a5c-ai (https://skillmd.com/u/a5c-ai)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/a5c-ai/huggingface-classifier

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# 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