bespokelabsai/nimble

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

What it does

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.

How it helps ATF

Harness can compare its request routing and condition checks for task execution decisions. LabChin can reference its shared data curation and training approach for decision-model research.

License

No license No license file found. Without a license, reuse of the code is not permitted by default.

More in this category

• 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.
• 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.
• dexmal/dexbotic
  A PyTorch toolbox for vision-language-action research covering pretraining, fine-tuning, inference, and evaluation. It provides multiple model configurations, a unified robot training data format, and deployment scripts.
• hr98w/jev-visual
  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.
• whitecircle/halo
  A training framework for language and multimodal models supporting pretraining, supervised fine-tuning, preference optimization, and asynchronous multi-turn reinforcement learning. It runs Hugging Face models on one GPU or across nodes.

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.