| # Evaporate | |
| Datasets for paper "Evaporate: Language Models Enable Simple Systems for Generating Structured Views of Heterogeneous Data Lakes". | |
| The best way to use this data is by cloning: | |
| ``` | |
| git lfs install | |
| git clone https://huggingface.co/datasets/hazyresearch/evaporate | |
| ``` | |
| We can then unzip everything using this code snippet: | |
| ``` | |
| import os | |
| data_path = "evaporate/data" | |
| # list paths in data_path | |
| data_path_files = os.listdir(data_path) | |
| for path in data_path_files: | |
| sub_path = f"{data_path}/{path}" | |
| # tar unzip 'docs.tar.gz' in the sub_paths | |
| if os.path.exists(f"{sub_path}/docs.tar.gz"): | |
| os.system(f"tar -xvf {sub_path}/docs.tar.gz -C {sub_path}") | |
| ``` | |