To launch an example:

# Recommended: YAML + CLI sky launch examples/<name>.yaml # Advanced: programmatic API python examples/<name>.py

Machine learning examples:

• dvc_pipeline.yaml: Use DVC to easily run ML pipelines on the cloud and version-control the results in git and cloud buckets. An existing DVC remote and DVC pipeline are prerequisites. A detailed tutorial is available here.

• huggingface_glue_imdb_app.yaml: Use Huggingface Transformers to finetune a pretrained BERT model.

• resnet_distributed_torch.yaml: Run Distributed PyTorch (DDP) training of ResNet50 on 2 nodes.

• detectron2_app.yaml: Run Detectron2 on a V100 GPU.

• TPU examples

  • tpu/tpu_app.yaml: Train on a TPU node on GCP. Finetune BERT on Amazon Reviews for sentiment analysis.
  • tpu/tpuvm_mnist.yaml: Train on a TPU VM on GCP. Train on MNIST in Flax (based on JAX).

• resnet_app.py: ResNet50 training on GPUs, adapted from tensorflow/tpu.

  The training data is currently a public, "fake_imagenet" dataset (gs://cloud-tpu-test-datasets/fake_imagenet, 70GB).

• resnet_distributed_tf_app.py: Distributed training variant of the above, via TensorFlow Distributed.

• huggingface_glue_imdb_grid_search_app.py: Grid search: run many trials concurrently on the same VM.

...and many more.

General examples:

• detectron2_docker.yaml: Using Docker to run Detectron2 on GPUs.

• using_file_mounts.yaml: Using file_mounts to upload local/cloud paths to a cluster.

• multi_hostname.yaml: Run a command on multiple nodes.

• env_check.yaml: Using environment variables in the run commands.

• multi_echo.py: Launch and schedule hundreds of bash commands on the clouds, with configurable resources. Similar to grid search.

...and many more.