Validate JSONL format for fine-tuning
Generate a Parquet file for dataset validation
A collection of parsers for LLM benchmark datasets
Browse and view Hugging Face datasets
Manage and orchestrate AI workflows and datasets
Label data efficiently with ease
Manage and analyze labeled datasets
Organize and process datasets using AI
Search narrators and view network connections
Transfer datasets from HuggingFace to ModelScope
Save user inputs to datasets on Hugging Face
Search and find similar datasets
Explore datasets on a Nomic Atlas map
GPT-Fine-Tuning-Formatter is a tool designed to validate and format JSONL datasets for fine-tuning GPT models. It ensures that your dataset adheres to the required structure and format, making it ready for model fine-tuning. This tool is essential for anyone preparing datasets for training or adjusting GPT models, as it helps identify and correct formatting issues before the fine-tuning process begins.
• JSONL Validation: Ensures that each line in your dataset is valid JSON.
• Error Detection: Identifies formatting issues such as missing fields or invalid structures.
• Data Preview: Provides a preview of your dataset to help you understand its structure.
• Auto-Correction: Automatically fixes common formatting errors.
• Custom Schema Support: Allows you to define a custom schema for advanced validation.
1. What happens if my JSONL file is invalid?
If your JSONL file is invalid, GPT-Fine-Tuning-Formatter will identify the errors and provide a detailed report. You can then fix these issues before proceeding with fine-tuning.
2. Can GPT-Fine-Tuning-Formatter fix errors automatically?
Yes, the tool includes an auto-correction feature that can fix common formatting errors. However, for complex issues, manual intervention may be required.
3. How do I use a custom schema with GPT-Fine-Tuning-Formatter?
You can define a custom schema in a separate JSON file and specify its path when running the tool. This allows you to enforce specific data structures beyond basic validation.