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tev1

Together AI's open recipe and weights for a Jev-inspired decision model fine-tuned on Qwen3.5-4B, with the full data pipeline, training config, and saved benchmark results.

togethercomputer/tev1

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Open-weight, Jev-inspired decision model finetuned on top of Qwen3.5 4B

GitHub stars
127
Forks
15
Primary language
Python
License
mit
Last pushed
Updated Sep 2026

Repo stats from the GitHub API, cached Sep 2026.Homepage

Category
Repos & SDKs
Format
—
Published by
Community
Author
Together AI
Added
2026-09-25
Last verified
2026-09-25

Highlights

  • Trained on 37,840 unique examples with 4,568 held out for validation.
  • LoRA SFT at rank 8 for one epoch, learning rate 5e-5, capped at 2,048 tokens per example.
  • Saved results: 880 of 1,000 main decisions and 300 of 300 policy-transfer decisions.
  • Weights are published on Hugging Face; Together's blog frames training your own classifier at about $17.
  • The model answers only the option letter, so returned logprobs are preferences, not calibrated confidence.

Quickstart

bash
uv sync --locked
uv run python fetch_sources.py
uv run python build_all.py

Watch out

Training needs a Together API key and `--launch` starts a billed job. The saved results reuse dev sets rather than untouched tests, and the dataset and weights carry their own terms separate from the MIT code.

Reactions & coverage

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X: deepseek-v4.1-flash-jev

Reddit: A walkthrough of routing between models with Jev.

Related terms

Glossary definitions related to this entry.

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