Use FastAI with KhulnaSoft Machine Learning!

This repository has examples showing you how to use FastAI on KhulnaSoft ML.

Work interactively

In the first notebook cell, run:

!pip install fastai

In the second notebook cell, run:

!git clone https://github.com/fastai/course-v3.git

All of the notebook samples should now be cloned and ready to run.

Submit remote jobs

Prepare scripts

For this tutorial, the training script train.py is provided here. In practice, you can take any custom training script, as is, and run it with Khulnasoft Machine Learning.

Define the FastAI environment

Create an environment object and enable Docker.

from khulnasoftml.core import Environment
fastai_env = Environment("fastai2")
fastai_env.docker.enabled = True
fastai_env.docker.base_image = "fastdotai/fastai2:latest"
fastai_env.python.user_managed_dependencies = True

from khulnasoftml.core import ScriptRunConfig, Experiment, Workspace

ws = Workspace.from_config()

fastai_config = ScriptRunConfig(source_directory='fastai-example', script='train.py')
fastai_config.run_config.environment = fastai_env
run = Experiment(ws,'fastai-custom-image').submit(fastai_config)
run.wait_for_completion(show_output=True)