Buckets:
| # Quickstart Guide | |
| [](https://colab.research.google.com/github/gradio-app/trackio/blob/main/examples/notebooks/quickstart.ipynb) | |
| To get started, you can run a simple example that logs some fake training metrics: | |
| ```python | |
| import trackio | |
| import random | |
| import time | |
| runs = 3 | |
| epochs = 8 | |
| for run in range(runs): | |
| trackio.init( | |
| project="my-project", | |
| config={"epochs": epochs, "learning_rate": 0.001, "batch_size": 64} | |
| ) | |
| for epoch in range(epochs): | |
| train_loss = random.uniform(0.2, 1.0) | |
| train_acc = random.uniform(0.6, 0.95) | |
| val_loss = train_loss - random.uniform(0.01, 0.1) | |
| val_acc = train_acc + random.uniform(0.01, 0.05) | |
| trackio.log({ | |
| "epoch": epoch, | |
| "train_loss": train_loss, | |
| "train_accuracy": train_acc, | |
| "val_loss": val_loss, | |
| "val_accuracy": val_acc | |
| }) | |
| time.sleep(0.2) | |
| trackio.finish() | |
| ``` | |
| Running the above will print to the terminal instructions on launching the dashboard. | |
| The usage of `trackio` is designed to be identical to `wandb` in most cases, so you can easily switch between the two libraries. | |
| ```py | |
| import trackio as wandb | |
| ``` | |
| ## Dashboard | |
| You can launch the dashboard by running: | |
| <hfoptions id="language"> | |
| <hfoption id="Shell"> | |
| ```sh | |
| trackio show | |
| ``` | |
| </hfoption> | |
| <hfoption id="Python"> | |
| ```py | |
| import trackio | |
| trackio.show() | |
| ``` | |
| </hfoption> | |
| </hfoptions> | |
| You can also provide an optional `project` name as the argument to load a specific project directly: | |
| <hfoptions id="language"> | |
| <hfoption id="Shell"> | |
| ```sh | |
| trackio show --project "my-project" | |
| ``` | |
| </hfoption> | |
| <hfoption id="Python"> | |
| ```py | |
| import trackio | |
| trackio.show(project="my-project") | |
| ``` | |
| </hfoption> | |
| </hfoptions> | |
| ## Deploying to Hugging Face Spaces | |
| When calling `trackio.init()`, by default the service will run locally and store project data on the local machine. | |
| But if you pass a `space_id` to [init()](/docs/trackio/pr_320/en/api#trackio.init), like: | |
| ```py | |
| trackio.init(project="my-project", space_id="orgname/space_id") | |
| ``` | |
| or | |
| ```py | |
| trackio.init(project="my-project", space_id="username/space_id") | |
| ``` | |
| it will use an existing or automatically deploy a new Hugging Face Space as needed. You should be logged in with the `huggingface-cli` locally and your token should have write permissions to create the Space. | |
| <EditOnGithub source="https://github.com/gradio-app/trackio/blob/main/docs/source/quickstart.md" /> |
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