Hi @oleh_v ,

You can try below approach, its supports data up to 2GB. For example using curl:

# Parameters
databricks_workspace_url="<databricks-workspace-url>"
personal_access_token="<personal-access-token>"
local_file_path="<local_file_path>"              # ex: /Users/foo/Desktop/file_to_upload.png
dbfs_file_path="<dbfs_file_path>"                # ex: /tmp/file_to_upload.png
overwrite_file="<true|false>"


curl --location --request POST https://${databricks_workspace_url}/api/2.0/dbfs/put \
     --header "Authorization: Bearer ${personal_access_token}" \
     --form contents=@${local_file_path} \
     --form path=${dbfs_file_path} \
     --form overwrite=${overwrite_file}

Upload large files using DBFS API 2.0 and PowerShell - Databricks

Hello Slash,

Thank you for your response. I'm encountering the same issue as described. I tried running the provided code in my Databricks workspace, but I received an error. My question is how the script is expected to access local files, especially since the file I’m trying to upload ("pytorch_model.bin") has both read and write permissions on my local machine.

Additionally, once I successfully upload the file to DBFS using the API, can I access and read the file directly from my code, or will I need to use a separate API to retrieve it?

Any guidance or clarification on these points would be greatly appreciated.

# Parameters
databricks_workspace_url="<url>"
personal_access_token="<token>"
local_file_path="C:\\Users\\<Username>\\Downloads\\pytorch_model.bin"
dbfs_file_path="pytorch_model.bin"
overwrite_file="true"