hr98w/jev-visual

Source
GitHub
First trending
Category
Model inference
GitHub stars
22
Main language
Python

This page introduces an external open-source repository. It is not an HDATF product.

hr98w/jev-visual

What it does

An educational Apple Silicon experiment using Qwen3.5 and MLX to answer multiple questions about one image by scoring candidate outputs. It includes a local browser interface, CLI and HTTP API.

How it helps ATF

LabChin can reference its visual classification demos and documented limitations when planning local vision experiments.

License

MIT Permissive. Commercial use and changes are allowed if the copyright notice is kept.

More in this category

  • featherless-ai/simple-jev
    Uses compatible open models for structured classification and scoring without training a separate classifier head. The server constructs JSON choices, rubric scores, or truth and support judgments from next-token logits rather than generated JSON text.
  • anthropics/uplifting-biomolecular-modeling
    A reference collection of inference optimization kits for protein and genomics machine-learning tools at pinned upstream versions. The release is not maintained and does not accept contributions.
  • bespokelabsai/nimble
    A typed-decision model project sharing data curation, training, and serving methods. Given text and a question schema, it returns selected choices or true-or-false answers with probabilities for allowed answers.
  • TheoLeeCJ/openjev
    An open-model experiment that reads typed option probabilities directly instead of generating answer text. It explores Jev's interface pattern rather than reproducing its undisclosed model or training.
  • NandhaKishorM/laya
    A multilingual decision engine that answers typed questions about text, email, tickets, or JSON in a single forward pass. A router selects a checkpoint for each request.

Only repositories in the ranked Trendshift lists are included, and the lists are used only to find candidates. We do not copy their ranks. Descriptions, licenses and star counts come from each GitHub repository. The notes are our own reading. We have not tested these projects, and a place on a trending list does not prove quality.

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