2.9.22
Released 28 Oct 2026
Official Model Ledger website
Machine Learning Projects on Windows
Model Ledger 2.9.22 runs on Windows 10/11 with an interface in 13 languages. It builds machine learning projects in your folder by running tools and showing results.
Find the most common label in my CSV and calculate the baseline accuracy.
- list_dir
.1 file - read_file
data.csvloaded - write_file
baseline.pysaved - Shell
python baseline.pyexit 0 - edit_file
baseline.py+2 lines
waiting for your OK before the next stepRejectAccept
34 MB
Setup program size
25 MB
Single .exe file
13
Interface languages
Windows 10/11
x64 architecture
Local
No telemetry data
Machine Learning Projects
Machine learning projects teach programs to find patterns in data, and the agent helps you build them in your own folder by running commands and showing real results. Start small. No account is needed to run the tool locally on your PC. The setup program is about 34 MB in size for Windows users.
First baseline for a small CSV project
list_dir inspects the project folder structure while read_file loads the data so you see the real results immediately and clearly for every machine learning project. Start now. write_file creates the baseline script to establish a performance benchmark for your python machine learning projects. Shell runs the training command and returns the exit code for each ml project. Model Ledger is version 2.9.22 for machine learning examples and projects. The diff to accept appears in Ask first mode before applying changes.
Tool trace
list_dir . → 1 file
read_file data.csv → loaded
write_file baseline.py → saved
shell python baseline.py → exit 0Explore machine learning project ideas
You can use the Shell tool to run terminal commands like linters and tests, and the agent returns the real output and exit code to confirm success in this workflow. This is practical. The edit_file tool shows every change as a diff before you accept in Ask first mode. You can search for machine learning project ideas using web_search to find topics for your work. The read_file tool inspects your scripts, and the list_dir tool shows the folder structure for version 2.9.22. You can create a mini project to test what you learned with these tools.
Tool trace
list_dir . → lists project files
read_file baseline.py → shows the script
grep "accuracy" baseline.py → 1 match
write_file results.csv → savedExecute ml projects locally
Local execution keeps your data safe because the agent uses Shell to run commands and checks the exit code for success in your folder. Use ml projects. The agent edits files with diffs so you verify the changes before they are applied. You can use read_file to inspect the project and grep to find where a setting is used. The agent records the results in the chat so you keep the project folder clean. The interface supports 13 languages for users around the world.
Build python machine learning projects
The agent uses read_file to inspect data and grep to find specific patterns, so you can verify the context before any changes are made. Review diffs carefully. Edit_file creates changes that appear as diffs for you to review carefully. Python is the usual language for these scripts and it is widely used for machine learning tasks. Shell runs commands to verify results with real exit codes and logs. This approach supports your project ideas effectively by keeping you in control since version 2.9.22.
How It Differs
Model Ledger v2.9.22 runs tools, so you see real output and every change for your ml final project advice. It runs tools.
| Typical chat assistant | Model Ledger | |
|---|---|---|
| Actions | Suggests actions | Runs actions |
| Output | Shows text | Shows real exit code |
| Files | Generates code | Writes to disk |
| Control | You copy and run the code yourself | Ask first mode |
How to Start
- Download the 34 MB setup file.
- Run the installer on Windows 10 or 11.
- Open the app and select your model.
- Start your first machine learning project.
Who Uses It and When
Beginners use Model Ledger to learn machine learning examples because the agent runs commands and you review the real output from each card to understand the results. Version 2.9.22 helps. It supports 13 languages and reads the file in the working folder.
In Ask first mode the diff waits for your OK, so you verify the change before it is applied to your project folder. Check it. You keep your workflow and control every step of the process.
Students use the agent to write scripts and run tests, so they keep their data local while staying responsible for the work they submit. No account needed. Data stays on the PC only with a local model.
Frequently Asked Questions
What are machine learning projects?
A machine learning project teaches a program to find patterns in data instead of following hand-written rules, so you define the problem and measure success by using your library with your dataset. Start now. Run the baseline and evaluate on unseen data to verify the model performance.
Is themlcode.com the official Model Ledger website?
Yes, themlcode.com is the official Model Ledger website where you download the installer and check its SHA-256 checksum against the published manifest to ensure integrity before running it on your Windows machine. Verify the hash. Use the Send feedback button for support if you need help.
Does Model Ledger train models for me?
No, Model Ledger does not train models for you because it runs your commands and shows the exit code while you provide the data and the library. You see every change. It executes your instructions.
What is Ask first mode?
Ask first is a mode that pauses before every action that changes something, so you review the edit before the agent executes it. It pauses. This keeps your project files safe until you decide to proceed with the changes.
Can the agent help with a regression project that predicts a number?
Yes, the agent helps write and run a regression script so that your code reports MAE or RMSE from the real run on your machine. Check the results. The agent keeps the logs for your records and ensures you have proof of the work.
How does privacy work with cloud models?
Secrets in tool output are redacted before they reach the model, and prompts go only to the endpoint you pick for safe processing of your data. It stays local. Your private information remains on the PC during every operation.
What is the file size?
The setup program is 34 MB and the portable single .exe is about 25 MB for Windows 10/11 with version 2.9.22 supporting 13 languages. Runs locally. No account needed to run the application on your own machine.
Start Your Project
Download Model Ledger for your machine learning projects because version 2.9.22 edits files and runs commands to show real results. Edit files.
Download Model Ledger for Windows ↗Quick Links
The pages of this website are available in 20 languages.
Product Overview ↗ Model Configuration ↗ Workflow Library ↗ Download Installer ↗ FAQ Page ↗ Privacy Policy ↗
