SaaS Metrics
jaredpalmer/kev
tiny Jev-like family of decision models built on top of Qwen3.5 you can train and run on your own
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tiny Jev-like family of decision models built on top of Qwen3.5 you can train and run on your own
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Deep-Dive FAQs
What is jaredpalmer/kev?
jaredpalmer/kev is a digital product or tool described as: tiny Jev-like family of decision models built on top of Qwen3.5 you can train and run on your own
Where did jaredpalmer/kev originate?
Data for jaredpalmer/kev was aggregated directly from the GitHub Open Source community ecosystem, representing raw developer and early-adopter sentiment.
When was jaredpalmer/kev publicly launched?
The initial public indexing or launch date for jaredpalmer/kev within our tracked developer communities was recorded on September 17, 2026.
How popular is jaredpalmer/kev?
jaredpalmer/kev has achieved measurable traction, logging over 6,607 traction score and facilitating 368 recorded discussions or engagements.
Which technical categories define jaredpalmer/kev?
Based on metadata extraction, jaredpalmer/kev is categorized under topics such as: decision-model, jev, qwen3.
Are there active development issues for jaredpalmer/kev?
Yes, we are currently tracking open architectural debates and bug reports for this project on GitHub. There are currently 1 active high-priority issues logged recently.
Are there open-source alternatives related to jaredpalmer/kev?
Yes, the GitHub ecosystem contains correlated projects. For example, a repository named gavamedia/deltafin shares highly similar architectural descriptions and topics.
How does the creator describe jaredpalmer/kev?
The original author or development team describes the product as follows: "tiny Jev-like family of decision models built on top of Qwen3.5 you can train and run on your own"
Active Developer Issues (GitHub)
Logged: Sep 20, 2026
Community Voice & Feedback
Reproduced, and thank you — this reorders the plan.
**Your arm, same 40 development `deadline` items, `jaredpalmer/kev-4b` bf16 on an M5:**
| arm | acc | predicts middle | level MAE | Brier |
|---|---|---|---|---|
| as shipped | 0.525 | 0.750 | 0.452 | 0.829 |
| + "The report arrived N days after/before the deadline." | **0.925** | 0.350 | 0.077 | 0.139 |
On a Qwen3.5-4B-based checkpoint I trained today with the same recipe, the same injection takes it to **1.000** (Brier 0.001).
Independent evidence pointing the same way: the *untrained* Qwen3.5-9B base gets 0.82 on these items zero-shot (letter logits), Qwen3.5-4B 0.68 — and after our LoRA training, the adapted backbone read through the plain LM head drops to 0.53. So the model arrives able to subtract dates and our training data erodes it; the readout is not where the skill is lost. PLAN.md's ranking (ordinal readout first) was wrong, and I agree with your point that it would mostly convert honest hedging into commitment.
**One...
**Your arm, same 40 development `deadline` items, `jaredpalmer/kev-4b` bf16 on an M5:**
| arm | acc | predicts middle | level MAE | Brier |
|---|---|---|---|---|
| as shipped | 0.525 | 0.750 | 0.452 | 0.829 |
| + "The report arrived N days after/before the deadline." | **0.925** | 0.350 | 0.077 | 0.139 |
On a Qwen3.5-4B-based checkpoint I trained today with the same recipe, the same injection takes it to **1.000** (Brier 0.001).
Independent evidence pointing the same way: the *untrained* Qwen3.5-9B base gets 0.82 on these items zero-shot (letter logits), Qwen3.5-4B 0.68 — and after our LoRA training, the adapted backbone read through the plain LM head drops to 0.53. So the model arrives able to subtract dates and our training data erodes it; the readout is not where the skill is lost. PLAN.md's ranking (ordinal readout first) was wrong, and I agree with your point that it would mostly convert honest hedging into commitment.
**One...
interesting! going to try this out!
very cool research dude keep up the good fight!!!
Discovery Source
GitHub Open Source Aggregated via automated community intelligence tracking.
Tech Stack Dependencies
No direct open-source NPM package mentions detected in the product documentation.
Media Tractions & Mentions
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Deep Research & Science
No direct peer-reviewed scientific literature matched with this product's architecture.