• Fine-Tune Llama 2 Models with Ray and DeepSpeed on OpenShift AI

• Admin access to an OpenShift cluster (CRC is fine)

• Installed OpenDataHub or RHOAI, enabled all Distributed Workload components

• Installed Go 1.21

• CODEFLARE_TEST_OUTPUT_DIR - Output directory for test logs
• CODEFLARE_TEST_TIMEOUT_SHORT - Timeout duration for short tasks
• CODEFLARE_TEST_TIMEOUT_MEDIUM - Timeout duration for medium tasks
• CODEFLARE_TEST_TIMEOUT_LONG - Timeout duration for long tasks

• FMS_HF_TUNING_IMAGE - Image tag used in PyTorchJob CR for model training

• ODH_NAMESPACE - Namespace where ODH components are installed to
• NOTEBOOK_USER_NAME - Username of user used for running Workbench
• NOTEBOOK_USER_TOKEN - Login token of user used for running Workbench
• NOTEBOOK_IMAGE - Image used for running Workbench

To download MNIST training script datasets from S3 compatible storage, use the environment variables mentioned below :

• AWS_DEFAULT_ENDPOINT - Storage bucket endpoint from which to download MNIST datasets
• AWS_ACCESS_KEY_ID - Storage bucket access key
• AWS_SECRET_ACCESS_KEY - Storage bucket secret key
• AWS_STORAGE_BUCKET - Storage bucket name
• AWS_STORAGE_BUCKET_MNIST_DIR - Storage bucket directory from which to download MNIST datasets.

Note : Either use

Execute tests like standard Go unit tests.

go test -timeout 60m ./tests/kfto/