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denis-pplx
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denis-pplx/autojev

Full-weight Qwen decision model with calibrated probabilities, training code, REST API, and playground.

Python ◇ calibration MIT
★115STARS
⑂10FORKS
!0ISSUES
🏆#13,670GLOBAL RANK
🔥10DAYS TRENDING
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Momentum

+10

STARS · LAST 30 DAYS

1

PER DAY

#1,743

MOST-STARRED Python

Window7 days30 days90 days
Stars gained+0+10+90
Per day111
Forks gained+0+3+10

autojev gained 10 stars in the last 30 days, about 1 a day, and now has 115. It is about 1 year old and has averaged roughly 115 stars a year. It ranks #1,743 among Python repositories and #13,670 across all languages on GitHubRepo.

Trending Record

autojev has maintained a continuous presence across global trending indexes, peaking at #682. Below is the 30-day activity profile:

💡 Overview

autojev is an open-source project written in Python: Full-weight Qwen decision model with calibrated probabilities, training code, REST API, and playground.

Engineered for speed, consistency, and developer ease, it solves common hurdles in calibration, classification, pytorch. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.

⚡ Key Features

1

Optimized execution pipeline written in Python for predictable speed.

2

Zero-friction configuration with comprehensive sensible defaults out of the box.

3

Cross-platform runtime support across Linux, macOS, and Windows environments.

4

Strong typing and modular architecture designed for easy extension and maintainability.

5

Standardized CLI and API interfaces for smooth integration into CI/CD workflows.

6

Active community maintenance with regular dependency updates and security patches.

📥 Installation

terminal
$ pip install autojev

⚙ System Requirements

Platforms

  • • macOS
  • • Linux
  • • Windows

Runtime & Dependencies

Python >= 3.9, pip, virtualenv

Architecture

x86_64, ARM64 (Apple Silicon & Graviton)

🧠 How It Works

autojev coordinates its core functionality through a modular Python pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.

🎯 Production Use Cases

Production System Integration

Embed autojev into Python backend services to handle core application logic.

CI/CD Automated Pipelines

Run automated validation, builds, and integration suites during deployments.

Developer Tooling & Workflows

Accelerate developer onboarding with pre-configured project utilities.

Open Source Extension

Fork and customize internal modules under the repository's open MIT license.

🚀 Getting Started

1

Install autojev using your package manager: `pip install autojev`

2

Initialize your project workspace or configuration file for autojev.

3

Import autojev into your codebase or invoke it directly from your terminal.

4

Execute your test suite or run `autojev --help` to verify successful setup.

👍 Strengths

Active community backing with 113 GitHub stars and verified adoption.
Permissive open-source distribution under the MIT license.
Built in Python for high execution speed and developer familiarity.
Cross-platform compatibility across modern Linux, macOS, and Windows environments.
Clean modular design allowing flexible configuration and pipeline integration.

⚠️ Considerations

Requires familiarity with Python and modern CLI workflows.
Ecosystem extensions may require manual configuration depending on environment constraints.
Active development roadmap means breaking API changes may occur across major versions.

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👥 Who Should Use This

Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.

🏆 Nearby in the Rankings

denis-pplx/autojev is currently ranked #13,670 by stars across every repository tracked on GitHubRepo. These are adjacent projects:

RankRepositoryLanguageStarsAction
#13,617 starroyhq/agentkib Rust ★ 116 Compare ↗
#13,617 Amakurai/dsh-liketavern TypeScript ★ 116 Compare ↗
#13,617 arronKler/pairfob TypeScript ★ 116 Compare ↗
#13,617 caomod2077/Deobfuscator-Luraph-V15 JavaScript ★ 116 Compare ↗
#13,617 howseen-ai/claude-motion-design Python ★ 116 Compare ↗
#13,670 denis-pplx/autojev This Project Python ★ 115
#13,670 mojombo/egitd Erlang ★ 115 Compare ↗
#13,670 mhartl/find_mass_assignment Ruby ★ 115 Compare ↗
#13,670 brown/protobuf C++ ★ 115 Compare ↗
#13,670 mnaberez/supervisor_twiddler Python ★ 115 Compare ↗
#13,670 alexrabarts/big_sitemap Ruby ★ 115 Compare ↗

Frequently Asked Questions

What does autojev do? +

Full-weight Qwen decision model with calibrated probabilities, training code, REST API, and playground.

What language is autojev written in? +

The primary language is Python. Topics include: calibration, classification, pytorch, qwen.

Is autojev actively maintained? +

Yes, the last recorded push was on Sep 22, 2026 with 0 open issues being tracked.

How many stars does autojev have? +

autojev has 115 stars and 10 forks on GitHub.

How does autojev rank among GitHub repositories? +

With 115 stars, denis-pplx/autojev is ranked #13,670 globally across all repositories tracked on GitHubRepo and #1,743 among Python projects.

What license is autojev distributed under? +

The repository reports a MIT license. Always verify the repository LICENSE file for legal terms.

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