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README.md
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@ -25,6 +25,7 @@ TRAINS is an auto-magical experiment manager that you can use productively with
preserving your existing methods and practices. Use it on a daily basis to boost collaboration and visibility,
or use it to automatically collect your experimentation logs, outputs, and data to one centralized server for provenance.
(See TRAINS live at [https://demoapp.trainsai.io](https://demoapp.trainsai.io))
![Alt Text](docs/webapp_screenshots.gif)
## Why Should I Use TRAINS?
@ -80,6 +81,7 @@ TRAINS magically logs the following:
## See for Yourself
We have a demo server up and running [https://demoapp.trainsai.io](https://demoapp.trainsai.io) (it resets every 24 hours and all of the data is deleted).
You can test your code with it:
1. Install TRAINS
@ -91,9 +93,12 @@ You can test your code with it:
from trains import Task
Task = Task.init(project_name=”my_projcet”, task_name=”my_task”)
1. Run your code. When TRAINS connects to the server, a link prints.
1. Run your code. When TRAINS connects to the server, a link prints. For example:
1. In the Web-App, view your parameters, model and tensorboard metrics.
TRAINS Metrics page:
https://demoapp.trainsai.io/projects/76e5e2d45e914f52880621fe64601e85/experiments/241f06ae0f5c4b27b8ce8b64890ce152/output/log
1. Open your link and view the experiment parameters, model and tensorboard metrics.
## How TRAINS Works