budgetml
ck
Our great sponsors
budgetml | ck | |
---|---|---|
4 | 9 | |
1,331 | 573 | |
0.1% | 2.4% | |
0.0 | 10.0 | |
about 2 months ago | 4 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
budgetml
ck
-
Asking for a favor to test modular ML benchmark for Student Cluster Competition
We would like to ask for a favor: we have prepared a tutorial to help students run the MLPerf inference benchmark across different platforms at the Student Cluster Competition at SuperComputing'22 in a few days: https://github.com/mlcommons/ck/blob/master/docs/tutorials/s... .
We would like to test it across different machines before students run it ;) . If you have time, please help us go through this tutorial and run this benchmark on any available system - it should not take more than 20..30 minutes.
If you encounter any issues, please report them at https://github.com/mlcommons/ck/issues so that we could fix them before the competition.
Thank you for supporting this community project!
-
[N] Open working group to modularize ML Systems
Just to let you know that we are preparing a new working group at MLCommons to help the community modularize ML/AI Systems and automate their benchmarking, optimization and deployment. It will be based on the MLPerf methodology and MLCommons "Collective Knowledge" automation meta-framework that was already used to automate recent MLPerf inference benchmark submissions from Qualcomm, HPE, Lenovo, Krai, DELL and OctoML. Please join the group here to provide your feedback and help with this community effort! Thank you!
-
Research software code is likely to remain a tangled mess
– Their solution product https://cknowledge.io/ and source code https://github.com/ctuning/ck\
I guess it should be helpful to the researchers community.
What are some alternatives?
pinferencia - Python + Inference - Model Deployment library in Python. Simplest model inference server ever.
zenml - ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
SmartSim - SmartSim Infrastructure Library.
onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
osmnx - OSMnx is a Python package to easily download, model, analyze, and visualize street networks and other geospatial features from OpenStreetMap.
dslinter - `dslinter` is a pylint plugin for linting data science and machine learning code. We plan to support the following Python libraries: TensorFlow, PyTorch, Scikit-Learn, Pandas and NumPy.
fastapi-template - Completely Scalable FastAPI based template for Machine Learning, Deep Learning and any other software project which wants to use Fast API as an API framework.
experta - Expert Systems for Python
aws-deployment-framework - The AWS Deployment Framework (ADF) is an extensive and flexible framework to manage and deploy resources across multiple AWS accounts and regions based on AWS Organizations.
FastAPI-template - Feature rich robust FastAPI template.
tritony - Tiny configuration for Triton Inference Server
frontends-team-compass - A repository for team interaction, syncing, and handling meeting notes across the JupyterLab ecosystem.