Trackio

_blog.yml

@@ -6383,3 +6383,13 @@
     - research
     - evaluation
     - ai
+
+- local: trackio
+  title: "Introducing Trackio: A Lightweight Experiment Tracking Library from Hugging Face"
+  thumbnail: /blog/assets/trackio/thumbnail.gif
+  author: abidlabs
+  date: July 18, 2025
+  tags:
+    - research
+    - gradio
+    - open-source

trackio.md

@@ -0,0 +1,119 @@
+---
+title: "Introducing Trackio: A Lightweight Experiment Tracking Library from Hugging Face"
+thumbnail: /blog/assets/trackio/thumbnail.gif
+authors:
+- user: abidlabs
+- user: znation
+---
+
+# Introducing Trackio: A Lightweight Experiment Tracking Library from Hugging Face
+
+If you have trained your own machine learning model, you know how important it is to be able to track metrics, parameters, and hyperparameters during training and visualize them afterwards to better understand your training run. 
+
+Most machine learning researchers use specific experiment tracking libraries to do this. However, these libraries can be paid, 
+
+... other reasons to switch to Trackio (science team?)
+
+That's why the Hugging Face open-source team is excited to introduce: `trackio`, a completely free, open-source Python library...
+
+## Installing
+
+You can install `trackio` using pip:
+
+```bash
+pip install trackio
+```
+
+Or, if you prefer using `uv`:
+
+```bash
+uv pip install trackio
+```
+
+## Usage
+
+`trackio` is designed to be a drop-in replacement for experiment tracking libraries like `wandb`. The API is compatible with `wandb.init`, `wandb.log`, and `wandb.finish`, so you can simply import `trackio` as `wandb` in your code. Here is an example:
+
+```python
+import trackio as wandb
+import random
+import time
+
+runs = 3
+epochs = 8
+
+def simulate_multiple_runs():
+    for run in range(runs):
+        wandb.init(project="fake-training", 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)
+            wandb.log({
+                "epoch": epoch,
+                "train_loss": train_loss,
+                "train_accuracy": train_acc,
+                "val_loss": val_loss,
+                "val_accuracy": val_acc
+            })
+            time.sleep(0.2)
+    wandb.finish()
+
+simulate_multiple_runs()
+```
+
+After logging your experiments, you can launch the dashboard to visualize your results. Run the following command in your terminal:
+
+```bash
+trackio show
+```
+
+Or, launch it from Python:
+
+```python
+import trackio
+trackio.show()
+```
+
+You can also specify a project name:
+
+```bash
+trackio show --project "my project"
+```
+
+Or in Python:
+
+```python
+trackio.show(project="my project")
+```
+
+To deploy the dashboard to Hugging Face Spaces, pass a `space_id` to `init`:
+
+```python
+trackio.init(project="fake-training", space_id="org_name/space_name")
+```
+
+If you are hosting your dashboard on Spaces, you can embed it anywhere using an iframe:
+
+```html
+<iframe src="https://abidlabs-trackio-1234.hf.space/?project=fake-training&metrics=train_loss,train_accuracy&sidebar=hidden" width=1600 height=500 frameBorder="0">
+```
+
+## Design Principles
+
+- API compatible with popular experiment tracking libraries, making migration both to and from Trackio seamless.
+- Local-first: logs and dashboards run and persist locally by default, with the option to host on Hugging Face Spaces.
+- Lightweight and extensible: the core codebase is under 1,000 lines of Python, making it easy to understand and modify.
+- Free and open-source: all features, including hosting on Hugging Face, are free.
+- Built on top of 🤗 Datasets and Spaces for robust data handling and visualization.
+
+## Limitations
+
+Trackio is intentionally lightweight and not intended to be a fully-featured experiment tracking solution. It is currently in beta, and the database schema may change, which could require migrating or deleting existing database files (by default at `~/.cache/huggingface/trackio`).
+
+Some features found in other tracking tools, such as artifact management, or complex visualizations, is available yet. Feedback and contributions are welcome as the project evolves.