[Q] How to turn off only model synching in huggingface integration about wandb HOT 10 OPEN

# # log the initial model and architecture to an artifact
# with tempfile.TemporaryDirectory() as temp_dir:
#     model_name = (
#         f"model-{self._wandb.run.id}"
#         if (args.run_name is None or args.run_name == args.output_dir)
#         else f"model-{self._wandb.run.name}"
#     )
#     model_artifact = self._wandb.Artifact(
#         name=model_name,
#         type="model",
#         metadata={
#             "model_config": model.config.to_dict() if hasattr(model, "config") else None,
#             "num_parameters": self._wandb.config.get("model/num_parameters"),
#             "initial_model": True,
#         },
#     )
#     model.save_pretrained(temp_dir)
#     # add the architecture to a separate text file
#     save_model_architecture_to_file(model, temp_dir)

#     for f in Path(temp_dir).glob("*"):
#         if f.is_file():
#             with model_artifact.new_file(f.name, mode="wb") as fa:
#                 fa.write(f.read_bytes())
#     self._wandb.run.log_artifact(model_artifact, aliases=["base_model"])

#     badge_markdown = (
#         f'[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge'
#         f'-28.svg" alt="Visualize in Weights & Biases" width="20'
#         f'0" height="32"/>]({self._wandb.run.get_url()})'
#     )

#     modelcard.AUTOGENERATED_TRAINER_COMMENT += f"\n{badge_markdown}"

I just commented out the following in the integration_utils.py of transformers of Hugginggface.

from wandb.

Hi @jubueche, could you please talk a bit about your workflow, and why you are interested in turning off the artifact logging ?

from wandb.

Hi,

I don't need to turn off the artifact logging. I just don't want my model to get synced to wandb. My models are multiple GB and it takes quite some space and time when I upload them.

from wandb.

Gotcha, could you please try setting os.environ["WANDB_LOG_MODEL"] = "false"

Here are our docs on it

from wandb.

Gotcha, could you please try setting os.environ["WANDB_LOG_MODEL"] = "false"

Here are our docs on it

This does not work.

from wandb.

@ArtsiomWB I can confirm. This does not work.

from wandb.

Hey @jubueche, thank you so much for the workaround. It is strange that os.environ["WANDB_LOG_MODEL"] = "false" is not working on your side. What version of wandb are you currently on? Will try reproducing this on my side.

from wandb.

Hi there, I wanted to follow up on this request. Please let us know if we can be of further assistance or if your issue has been resolved.

from wandb.

Hi sorry, my wandb version is

>>> wandb.__version__
'0.16.4'

For now I am just using the code with the commented out section.

from wandb.

# # log the initial model and architecture to an artifact
# with tempfile.TemporaryDirectory() as temp_dir:
#     model_name = (
#         f"model-{self._wandb.run.id}"
#         if (args.run_name is None or args.run_name == args.output_dir)
#         else f"model-{self._wandb.run.name}"
#     )
#     model_artifact = self._wandb.Artifact(
#         name=model_name,
#         type="model",
#         metadata={
#             "model_config": model.config.to_dict() if hasattr(model, "config") else None,
#             "num_parameters": self._wandb.config.get("model/num_parameters"),
#             "initial_model": True,
#         },
#     )
#     model.save_pretrained(temp_dir)
#     # add the architecture to a separate text file
#     save_model_architecture_to_file(model, temp_dir)

#     for f in Path(temp_dir).glob("*"):
#         if f.is_file():
#             with model_artifact.new_file(f.name, mode="wb") as fa:
#                 fa.write(f.read_bytes())
#     self._wandb.run.log_artifact(model_artifact, aliases=["base_model"])

#     badge_markdown = (
#         f'[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge'
#         f'-28.svg" alt="Visualize in Weights & Biases" width="20'
#         f'0" height="32"/>]({self._wandb.run.get_url()})'
#     )

#     modelcard.AUTOGENERATED_TRAINER_COMMENT += f"\n{badge_markdown}"

I just commented out the following in the integration_utils.py of transformers of Hugginggface.

Do you know if this was a new addition to transformers? Maybe the problem is on their side? This problem doesn't arise for me on a different system which has an older version of transformers.

from wandb.