ProjectDMX/DMI

Source
GitHub
First trending
Category
Model inference
GitHub stars
56
Main language
Python

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

ProjectDMX/DMI

What it does

A decoupled, asynchronous observability backend for LLM inference and training that exposes internal model states. It is a research preview with HuggingFace, vLLM and Megatron-LM integrations, and its APIs may change.

License

Apache-2.0 Permissive, with a patent grant. Commercial use is allowed; keep the notices and state your changes.

More in this category

  • magnitudedev/magnitude
    An inference engine for agents that compiles and tunes kernels on the user's hardware. It runs open models on Apple Silicon, NVIDIA, AMD or CPU and connects to existing agents through a desktop app and CLI.
  • ninjahawk/livenerf
    A longitudinal benchmark for detecting model capability drift after release. It uses frozen prompts, a pinned CLI, fixed graders and retained raw logs.
  • Vibra-Ingenn/Janus
    A single Go binary that runs gguf models on a local machine, using llama.cpp through Vulkan on AMD, Intel or NVIDIA graphics with a CPU fallback, and exposes an OpenAI compatible API for chat completions and models. It swaps models without a restart, splits reasoning output into its own field, and reads the chat template from gguf metadata, with no Python and no Docker required.
  • deepopen-com/deepopen
    A non-autoregressive engine built on Laya for multilingual structured decisions. It performs multidimensional classification in a single forward pass.
  • Edge0-AI/Edge0
    Edge0 is a streaming MoE inference framework using SSD expert offloading, Recover-LoRA and routing prediction. Its README distinguishes released platform engines from a unified framework planned for Q4 2026.

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.

View on GitHub (opens in a new tab)