| license: apache-2.0 | |
| task_categories: | |
| - reinforcement-learning | |
| language: | |
| - en | |
| tags: | |
| - eda | |
| - analog | |
| - rl | |
| pretty_name: OSIRIS Dataset | |
| # OSIRIS: Bridging Analog Layout Circuit Design and Machine Learning with Scalable Dataset Generation | |
| **OSIRIS** is an end-to-end analog circuits design pipeline capable of producing, validating, and evaluating layouts for generic analog circuits. | |
| The [Osiris 🤗 HuggingFace repository](https://huggingface.co/datasets/anonymousUser2/osiris) hosts the OSIRIS code and dataset generated following random exploration discussed in the paper. | |
| - **Curated by:** Anonymous | |
| - **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 code is stored in `osiris_code.zip` while the dataset is stored in `Osiris_Dataset.zip`. | |
| ```python | |
| from huggingface_hub import hf_hub_download | |
| file_path = hf_hub_download( | |
| repo_id="anonymousUser2/osiris", | |
| filename=<filename_to_download>, | |
| repo_type="dataset", | |
| local_dir=<download_path> | |
| ) | |
| ``` | |
| Where `<filename_to_download>` is either `osiris_code.zip` or `Osiris_Dataset.zip` and `<download_path>` is the path to your local folder. | |
| ## Note | |
| This repository is protected by copyright and licensed under the Apache-2.0 license. |