@<1698868530394435584:profile|QuizzicalFlamingo74> did u find solution?)

I think based on the src file dataset.py the compression False is not possible

def upload(
        self,
        show_progress=True,
        verbose=False,
        output_url=None,
        compression=None,
        chunk_size=None,
        max_workers=None,
        retries=3,
    ):
        # type: (bool, bool, Optional[str], Optional[str], int, Optional[int], int) -> ()
        """
        Start file uploading, the function returns when all files are uploaded.

        :param show_progress: If True, show upload progress bar
        :param verbose: If True, print verbose progress report
        :param output_url: Target storage for the compressed dataset (default: file server)
            Examples: `

`, `

` , `

` , `/mnt/share/data`
        :param compression: Compression algorithm for the Zipped dataset file (default: ZIP_DEFLATED)
        :param chunk_size: Artifact chunk size (MB) for the compressed dataset,
            if not provided (None) use the default chunk size (512mb).
            If -1 is provided, use a single zip artifact for the entire dataset change-set (old behaviour)
        :param max_workers: Numbers of threads to be spawned when zipping and uploading the files.
            If None (default) it will be set to:

          - 1: if the upload destination is a cloud provider ('s3', 'gs', 'azure')
          - number of logical cores: otherwise
        :param int retries: Number of retries before failing to upload each zip. If 0, the upload is not retried.

        :raise: If the upload failed (i.e. at least one zip failed to upload), raise a `ValueError`
        """

@<1706116294329241600:profile|MinuteMouse44> unfortunately no, I created my own upload method with python Django and passed the S3 directories to the clearML dataset to track of datasets.

Hi @<1698868530394435584:profile|QuizzicalFlamingo74> , Try compression=False

Which is not an ideal solution but for now it's working.