smcleish/scaling-laws-cache

This dataset is my cache for the scaling-laws related to the gemstone models.

In data_cache is the approach 3 data cache with the mins for delta=1e-4, the mins for delta=1e-3 are in mins_1e-3.

This is the code I used to upload it:

import pandas as pd
from datasets import Dataset
import os
import gc


def get_data_dict(path):
    contents = os.listdir(path)

    ds_store = {}
    for i, file in enumerate(contents):
        gc.collect()
        df = pd.read_parquet(f"{path}{file}")
        for col in df.columns:
            if pd.api.types.is_interval_dtype(df[col]):
                df[col] = df[col].astype(str)

        hf_dataset = Dataset.from_pandas(df)
        ds_store[file.replace(".parquet", "")] = hf_dataset
        hf_dataset.push_to_hub(
            "smcleish/scaling-laws-cache",
            private=True,
            data_dir=path.split("/")[1] + "/" + file.replace(".parquet", ""),
        )
        gc.collect()


ds_1 = get_data_dict("plotters/data_cache/")
ds_2 = get_data_dict("plotters/mins_1e-3/")

To download it do the oppostite of this. The cache is very large, so maybe target specific files you would like. The approach 3 code is expecting pandas .parquet files. Please open a discussion with any questions as this is currently very experimental.