Skip to content

Commit

Permalink
add a tutorial table
Browse files Browse the repository at this point in the history
  • Loading branch information
@allenanie
allenanie committed Oct 31, 2024
1 parent ef657de commit a174688
Showing 1 changed file with 7 additions and 7 deletions.
14 changes: 7 additions & 7 deletions README.md
View file
Original file line number Diff line number Diff line change
Expand Up @@ -129,13 +129,13 @@ Then, we can use the familiar PyTorch-like syntax to conduct the optimization.

## Tutorials

| **Level** | **Tutorial** | **Run in Colab** | **Description** |
| --- |--------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Beginner | [**Getting Started**](https://microsoft.github.io/Trace/quickstart/quick_start.html) | [<img align="center" src="https://colab.research.google.com/assets/colab-badge.svg" />](https://colab.research.google.com/github/microsoft/Trace/blob/website/docs/quickstart/quick_start.ipynb) | Introduces basic primitives like `node` and `bundle`. Showcases a code optimization pipeline. |
| Beginner | [**Adaptive AI Agent**](https://microsoft.github.io/Trace/quickstart/quick_start_2.html) | [<img align="center" src="https://colab.research.google.com/assets/colab-badge.svg" />](https://colab.research.google.com/github/microsoft/Trace/blob/website/docs/quickstart/quick_start_2.ipynb) | Introduce primitive `model` that allows anyone to build self-improving agents that react to environment feedback. Shows how an LLM agent learns to place a shot in a Battleship game.
| Intermediate | [**Multi-Agent Collaboration**](https://microsoft.github.io/Trace/quickstart/virtualhome.html) | N/A | Demonstrates how Trace can be used for multi-agent collaboration environment in Virtualhome.
| Intermediate | [**NLP Prompt Optimization**](https://microsoft.github.io/Trace/examples/nlp/bigbench_hard.html) | [<img align="center" src="https://colab.research.google.com/assets/colab-badge.svg" />](https://colab.research.google.com/github/microsoft/Trace/blob/website/docs/examples/nlp/bigbench_hard.ipynb) | Shows how Trace can optimizes prompt and code together jointly for BigBench-Hard 23 tasks.
| Advanced | [**Robotic Arm Control**](https://microsoft.github.io/Trace/examples/robotics/metaworld.html) | [<img align="center" src="https://colab.research.google.com/assets/colab-badge.svg" />](https://colab.research.google.com/github/microsoft/Trace/blob/website/docs/examples/robotics/metaworld.ipynb) | Trace can optimize code to control a robotic arm after observing a full trajectory of interactions. |
| **Level** | **Tutorial** | **Run in Colab** | **Description** |
| --- |-------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Beginner | [Getting Started](https://microsoft.github.io/Trace/quickstart/quick_start.html) | [<img align="center" src="https://colab.research.google.com/assets/colab-badge.svg" />](https://colab.research.google.com/github/microsoft/Trace/blob/website/docs/quickstart/quick_start.ipynb) | Introduces basic primitives like `node` and `bundle`. Showcases a code optimization pipeline. |
| Beginner | [Adaptive AI Agent](https://microsoft.github.io/Trace/quickstart/quick_start_2.html) | [<img align="center" src="https://colab.research.google.com/assets/colab-badge.svg" />](https://colab.research.google.com/github/microsoft/Trace/blob/website/docs/quickstart/quick_start_2.ipynb) | Introduce primitive `model` that allows anyone to build self-improving agents that react to environment feedback. Shows how an LLM agent learns to place a shot in a Battleship game.
| Intermediate | [Multi-Agent Collaboration](https://microsoft.github.io/Trace/quickstart/virtualhome.html) | N/A | Demonstrates how Trace can be used for multi-agent collaboration environment in Virtualhome.
| Intermediate | [NLP Prompt Optimization](https://microsoft.github.io/Trace/examples/nlp/bigbench_hard.html) | [<img align="center" src="https://colab.research.google.com/assets/colab-badge.svg" />](https://colab.research.google.com/github/microsoft/Trace/blob/website/docs/examples/nlp/bigbench_hard.ipynb) | Shows how Trace can optimizes prompt and code together jointly for BigBench-Hard 23 tasks.
| Advanced | [Robotic Arm Control](https://microsoft.github.io/Trace/examples/robotics/metaworld.html) | [<img align="center" src="https://colab.research.google.com/assets/colab-badge.svg" />](https://colab.research.google.com/github/microsoft/Trace/blob/website/docs/examples/robotics/metaworld.ipynb) | Trace can optimize code to control a robotic arm after observing a full trajectory of interactions. |


## Supported Optimizers
Expand Down

0 comments on commit a174688

Please sign in to comment.