Together AI Blog ·
Hassan El Mghari describes fine-tuning a Jev-like classifier based on Qwen3.5 4B and deploying it on Together’s serverless platform. The guide gives the example dataset size, estimated training cost, and approximate training time. Read 3 viewpoints with supporting evidence and source links.
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Using only 38,340 examples keeps fine-tuning costs low—approximately $17.0—while larger datasets increase both cost and training time.
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We only use 38,340 examples to keep our fine-tuning costs low. Training against a dataset of this size will only cost about $17.0, while larger datasets are more expensive and time-consuming to train against.
Hassan El Mghari · Paragraph 24
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fine-tuning cost efficiency →The fine-tuning job takes approximately 25 minutes to complete.
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The training job will take roughly 25 minutes to complete, and once it does we’ll have a model that is ready to do classification.
Hassan El Mghari · Paragraph 43
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training duration →The Jev-like classifier was launched on Together’s serverless platform, using Qwen3.5 4B as the base model.
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We just launched our own Jev-like classifier, together/Tev1-4B-experimental , on top of Qwen3.5 4B on Together’s serverless platform. In this blog post we’ll show you how to fine-tune your own version!
Hassan El Mghari · Paragraph 3
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model deployment platform →Attributed passages with the context to verify them. Open the original text to check the source.
Original excerpt
The training job will take roughly 25 minutes to complete, and once it does we’ll have a model that is ready to do classification.
Original excerpt
We only use 38,340 examples to keep our fine-tuning costs low. Training against a dataset of this size will only cost about $17.0, while larger datasets are more expensive and time-consuming to train against.
Original excerpt
We just launched our own Jev-like classifier, together/Tev1-4B-experimental , on top of Qwen3.5 4B on Together’s serverless platform. In this blog post we’ll show you how to fine-tune your own version!
El Mghari states that Qwen3.5 4B was used as the base model for their new Jev-like classifier on Together's platform.
Read supporting evidence · Hassan El MghariThe article announces the launch of together/Tev1-4B-experimental, a Jev-like classifier built on top of Qwen3.5 4B.
Read supporting evidence · Hassan El MghariThese viewpoints are linked to their original sources. Paraphrases are labeled and are not verbatim quotes.
Open transcript or source material (opens in a new tab)Report an issueHassan El Mghari on fine-tuning cost efficiency, model deployment platform, training duration. Explore 3 viewpoints by topic, with evidence from 1 source.