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- Last pushed
- Updated Oct 2026
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Jev directory
CommunityJev Tools & CLIs
Jev Account Filter
A tool for screening video-platform accounts with decision models, aimed at dataset collection: find relevant sources, then build a domain dataset from them. The README subtitles it decision models for video-platform account screening and links installation, commands and configuration docs.
- Stars
- 4
- Language
- HTML
- Reading time
- 2 min
- Published by
- Community
- Author
- caiweihan
- Last verified
- Oct 2026
- Platforms
- CLI
- Capabilities
- Open source
Highlights
- Banner describes it as decision models for video-platform account screening: find the accounts, build the dataset.
- Aimed at dataset construction: identify relevant accounts first, then select videos for training data.
- The README markets it as fast, cheap, accurate, flexible and promising, and links installation, commands and configuration docs.
- Screens video-platform accounts where user-generated content offers real-world material for model training.
- Created 2026-10-15 and pushed 2026-10-17, 4 stars; no license appears in the repository metadata.
Watch out
README reviewed 2026-10-17; the digest excerpt covers the banner and the introduction but no commands, configuration or results, and the repository shows an HTML language and no license.
Questions about this entry
Short answers drawn from the linked project or page.
A tool whose banner calls it decision models for video-platform account screening. Its stated purpose is to find accounts relevant to a domain and start dataset collection with better sources.
The repository name and README banner name Jev and describe the approach as screening accounts with decision models, but the digest excerpt does not show the specific Jev calls, questions or models used.
The README describes a common collection pipeline: first identify relevant accounts on a video platform, then use video models and human review to select individual videos suitable for training data.
The README links docs/installation.md, docs/commands.md and docs/configuration.md, so the project ships separate documentation pages. The digest excerpt does not include their contents.
Not documented in the digest. The repository shows no license in its GitHub metadata and is listed with an HTML language, with no requirements or setup section in the excerpt as of 2026-10-17.
The README uses badges that say fast, cheap, accurate, flexible and promising, but the digest shows no numbers, benchmarks or pricing for the screening itself.
The GitHub user caiweihan. The repository was created 2026-10-15 and last pushed 2026-10-17, with 4 stars and no forks when the sweep ran.
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