1 link tagged with all of: jev + fine tuning + deployment
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Together AI walks through building and deploying a Jev-like classification model on Qwen 3.5 4B for $17. The guide covers dataset selection, fine-tuning, and deploying the model behind an HTTP endpoint so you can query it for tasks like intent detection or sentiment analysis.
- You can fine-tune a working classification model on 38,000 examples for roughly $17 and have it deployed in 25 minutes using Together's platform
- The model accepts JSON-formatted state plus predefined questions and returns structured answers (scores, booleans, or multiple choice), making it practical for e-commerce returns, paper categorization, or sentiment rating
- The entire process is automated through provided scripts—you clone a repo, download datasets, run a training command, and get back a deployed API endpoint ready to integrate