Fine Tuning Job Lifecycle
Together AI · Together AI
Together AI evals — Fine-Tuning Job Lifecycle (relift v3)
About Together AI
Together AI is an enterprise AI inference cloud providing fast, scalable access to leading open-source models via an OpenAI-compatible API. Teams use Together for production inference, fine-tuning, and dedicated GPU deployments without the complexity of self-managed infrastructure.
Sample tests· showing 3 of 8
| # | Input | Expected behavior | Check |
|---|---|---|---|
| 01 | Job should fail fast in validation before GPU spend [REQUIRES-VERIFICATION on exact API error code]. | Validate JSONL locally; fix malformed records; resubmit; document that failed validation should not bill GPU hours. | Pass / FailAi Platformhigh |
| 02 | Quickstart mentions LoRA, DPO, full—pick LoRA for small data unless quality requires full [REQUIRES-VERIFICATION]. | Recommend LoRA for 500-example start; plan eval harness on held-out set; tag SKU-specific limits as unverified. | Pass / FailAi Platformmedium |
| 03 | Fine-tune must filter toxic/poison rows before upload. | {"criteria": ["Detects malicious instruction row", "Quarantines or removes before train", "Documents human review gate"], "pass_threshold": 2} | Pass / FailAi Platformcriticalneg. control |
Rubric criteria
- Together Ai
- Ai Platform
- Fine Tuning Job Lifecycle
Recommended for
Works with
Related evals
Run this eval in your workspace
Connect your data, configure thresholds, and review results with your team.