AI dataset JSONL validator
Validate chat message structures in a JSONL dataset.
AI dataset JSONL validator
Kā lietot AI dataset JSONL validator
AI dataset JSONL validator checks each line of a JSONL chat dataset for a valid structure. Every row must be a JSON object with a nonempty messages array, and each message needs a role of system, user, assistant or tool plus string content. It reports each row's status and message count along with totals of valid and invalid rows.
- Paste the source into the input editor, or load the built-in example.
- Check the source format before running the operation.
- Run ai dataset jsonl validator, review the output, then use the available copy or download controls.
Ko šis rīks atbalsta
Validate chat message structures in a JSONL dataset.
Ierobežojumi un apstrāde
Browser file and text limits apply, along with the bounds shown in Settings. Image processing is capped at 32 megapixels. OCR quality depends on source resolution and layout.
Piemēra avots
{"messages":[{"role":"user","content":"Hello"},{"role":"assistant","content":"Hi"}]}Biežāk uzdotie jautājumi
How do I validate a JSONL file for fine-tuning?
Paste the JSONL content with one JSON object per line. The table shows each row number, Valid or the specific error, and how many messages the row contains.
Which message roles does the JSONL validator accept?
Roles must be system, user, assistant or tool. A message with any other role, or with content that is not a string, is marked with an invalid role or content error.
Does the JSONL validator check a provider's exact format?
No. It checks the chat message structure only. It does not judge training quality or check provider-specific schemas, so review those rules separately. Between 1 and 10,000 nonempty rows are accepted.
Where is my input processed?
Processes source in your browser. Copy and download are explicit actions; source is not saved to account history.
What are the input limits?
Browser file and text limits apply, along with the bounds shown in Settings. Image processing is capped at 32 megapixels. OCR quality depends on source resolution and layout.