SHshcheklein·Feb 2, 2023Submission
MLEM: Open-source tool to package, serve, and deploy ML models on any platform
2 points · Open discussioniterative
mlem
Python2022–2023
iterative / mlem · Archived
mlem
🐶 A tool to package, serve, and deploy any ML model on any platform. Archived to be resurrected one day🤞
Developer ToolsCommand LineScience & EngineeringAI & Machine LearningLearning & ReferenceDevOps & Cloud
2Distinct people
5Mentions
0Explicit recommenders
720GitHub stars
What to know before exploring
What it is
🐶 A tool to package, serve, and deploy any ML model on any platform. Archived to be resurrected one day🤞
GitHub
Where it is used
No documented product use has been verified yet.
What people are saying
No recommendation phrase was found in the indexed comments.
No classified warning is attached to this page. Read the discussions before treating silence as approval.
Also in these discussions
No other repository is repeatedly linked in the same discussions.
This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 1:49:46 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by month5 dated mentions
Observed mentions: 2022-06-01 14:36:10 UTC to 2023-02-02 17:26:44 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| Jun 2022 | 2022-06-01 00:00:00 UTC | 2022-07-01 00:00:00 UTC | 2 | 2 | 0 |
| Jul 2022 | 2022-07-01 00:00:00 UTC | 2022-08-01 00:00:00 UTC | 0 | 0 | 0 |
| Aug 2022 | 2022-08-01 00:00:00 UTC | 2022-09-01 00:00:00 UTC | 0 | 0 | 0 |
| Sep 2022 | 2022-09-01 00:00:00 UTC | 2022-10-01 00:00:00 UTC | 0 | 0 | 0 |
| Oct 2022 | 2022-10-01 00:00:00 UTC | 2022-11-01 00:00:00 UTC | 0 | 0 | 0 |
| Nov 2022 | 2022-11-01 00:00:00 UTC | 2022-12-01 00:00:00 UTC | 1 | 1 | 0 |
| Dec 2022 | 2022-12-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 0 | 0 | 0 |
| Jan 2023 | 2023-01-01 00:00:00 UTC | 2023-02-01 00:00:00 UTC | 1 | 0 | 1 |
| Feb 2023 | 2023-02-01 00:00:00 UTC | 2023-03-01 00:00:00 UTC | 1 | 1 | 0 |
What Hacker News says
5 sourcesNo, it's a completely separate open source tool, not directly related to DVC - https://github.com/iterative/mlem
In Open-source tool to simplify ML model deploymentTool to package, serve, and deploy any ML model on any platform
1 points · Open discussionOpen source tool to package and deploy models
9 points · Open discussionShow HN: MLEM – ML model deployment tool
Hi, I'm one of the project creators. MLEM is a tool that helps you deploy your ML models. It’s a Python library + Command line tool.
1. MLEM can package an ML model into a Docker image or a Python package, and deploy it to, for example, Heroku.
2. MLEM saves all model metadata to a human-readable text file: Python environment, model methods, model input & output data schema and more.
3. MLEM helps you turn your Git repository into a Model Registry with features like ML model lifecycle management.
Our philosophy is that MLOps tools should be built using the Unix approach - each tool solves a single problem, but solves it very well. MLEM was designed to work hands on hands with Git - it saves all model metadata to a human-readable text files and Git becomes a source of truth for ML models. Model weights file can be stored in the cloud stora
Read the rest
ge using a Data Version Control tool or such - independently of MLEM.
Please check out the project: https://github.com/iterative/mlem and the website: https://mlem.ai
I’d love to hear your feedback!