Run your scripts
The agent creates and runs your conversion scripts, then shows the output.
Product
quantization neural network agent for Windows
01
ModelTrim is an autonomous agent that helps you perform tasks with a quantization neural network model on your own projects. It runs your scripts and shows their real results directly on your system.
Manage files
It reads, writes, and edits your Python files and logs inside the chat folder.
Check results
It runs your evaluation commands and shows the real exit code and output.
Features for your workflow
- Filesread, write, edit, delete, and search files directly in your working folder.
- Shellrun terminal commands and see the real exit code and output.
- Websearch the web or fetch documentation pages for your library.
- Screenshots and imagesuse OCR on screenshots or generate image files.
- Orchestrationrun parallel sub-agents or send hard steps to bigger models.
- Approval modesuse Auto-run, Ask first, or Plan only for your control.
- Cronschedule prompts to run on a specific schedule automatically.
- Modelsconnect to a cloud provider or a local model on your PC.
How the agent helps
The agent does not quantize a model itself; your script or library does the work.
Create a script to estimate weight size at different bit counts.
- write_file
size_estimate.pysaved - edit_file
size_estimate.pyedited - Shell
python size_estimate.pyexit 0 - read_file
size_estimate.pyread - Shell
python size_estimate.pyexit 0
waiting for your OK before the next stepRejectAccept
Walkthroughs
Estimate model size
You ask the agent to estimate the weight size of a made-up model at 32, 16, 8, and 4 bits, and the agent uses write_file to create a script with plain arithmetic. It runs. You review the script in Ask first mode before accepting the changes. Pruning and distillation are separate techniques that can be combined with quantization. You must measure quality before choosing a compression path for your model. Exploring pruning vs very low quantization helps you decide the best compression path. This process demonstrates quantization neural network techniques for your team. Deep learning model compression trades some quality for a smaller file.
Run conversion script
The agent writes your evaluation script with write_file and Ask first mode shows the diff so you can review changes before accepting them. Shell runs it. You see the real output and exit code in the chat. This ensures you control the evaluation process on your own system. When you need quantization guidance, the agent helps you measure quality and speed. This approach supports deep learning model compression by keeping your original model file untouched. Actions appear in the chat as cards with their results. You can read the logs with read_file and grep to verify the data.
What ModelTrim does not do
ModelTrim is not a hosted service or plugin; it is meant only for your own files, PC and servers you are authorised to use. It does not quantize a model itself, your conversion script does, and it does not enforce scope, so you keep work to your own models and systems, which is why you might ask what is the best model to fine tune with quantization.
