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---
license: apache-2.0
task_categories:
- reinforcement-learning
language:
- en
tags:
- eda
- analog
pretty_name: Osiris Dataset
---
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It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1). -->
# Osiris: A Scalable Dataset Generation Pipeline for Machine Learning in Analog Circuit Design
**Osiris** is an end-to-end analog circuits design pipeline capable of producing, validating, and evaluating layouts for generic analog circuits.
The [Osiris GitHub repository](https://github.com/hardware-fab/osiris) hosts the code that implements the randomized pipeline as well as the reinforcement learning-driven baseline methodology discussed
in the paper proposed at the NeurIPS 2025 Datasets & Benchmarks Track.
The [Osiris 🤗 HuggingFace repository](https://huggingface.co/datasets/hardware-fab/osiris) hosts the randomly generated dataset discussed in the paper.
- **Curated by:** hardware-fab
- **License:** Open Data Commons License [cc-by-4.0](https://huggingface.co/datasets/choosealicense/licenses/blob/main/markdown/cc-by-4.0.md)
## How to Download
The dataset is stored in `Osiris_Dataset.tar`.
```python
from huggingface_hub import hf_hub_download
file_path = hf_hub_download(
repo_id="hardware-fab/osiris",
filename="Osiris_Dataset.tar",
repo_type="dataset",
local_dir=<download_path>
)
```
## Note
This repository is protected by copyright and licensed under the [Apache-2.0 license](https://github.com/hardware-fab/chameleon/blob/main/LICENSE) file.
© 2025 hardware-fab
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