Prompt
Check a dataset before analysis
Find missing values, inconsistent formats, duplicates, and questions that could invalidate results.
ClaudeChatGPTGeminiData & Analytics
Dave AI
HuggingFace Classifier Skill
Hugging Face transformer model fine-tuning and inference for intent classification
instructions.md
--- name: huggingface-classifier-d97791bb3386 description: Hugging Face transformer model fine-tuning and inference for intent classification allowed-tools: - Read - Write - Edit - Bash - Glob - Grep 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--- name: huggingface-classifier-d97791bb3386 description: Hugging Face transformer model fine-tuning and inference for intent classification allowed-tools: - Read - Write - Edit - Bash - Glob - Grep 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
Platform guidance
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.