Getting error for not updating the gradio

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I am getting this runtime error for my demo: VQAScore - a Hugging Face Space by zhiqiulin

Exit code: 1. Reason: IMPORTANT: You are using gradio version 4.31.2, however version 5.0.1 is available, please upgrade.

ZeroGPU tensors packing: 0%| | 0.00/6.32G [00:00<?, ?B/s]e[A
ZeroGPU tensors packing: 0%| | 0.00/6.32G [00:00<?, ?B/s]
Traceback (most recent call last):
File “/home/user/app/app.py”, line 193, in
demo_vqascore_ranking.launch(share=False)
File “/usr/local/lib/python3.10/site-packages/spaces/zero/gradio.py”, line 142, in launch
task(*task_args, **task_kwargs)
File “/usr/local/lib/python3.10/site-packages/spaces/zero/torch/patching.py”, line 339, in pack
_pack(Config.zerogpu_offload_dir)
File “/usr/local/lib/python3.10/site-packages/spaces/zero/torch/patching.py”, line 331, in _pack
pack = pack_tensors(originals, fakes, offload_dir, callback=update)
File “/usr/local/lib/python3.10/site-packages/spaces/zero/torch/packing.py”, line 110, in pack_tensors
os.posix_fallocate(fd, 0, total_asize)
OSError: [Errno 28] No space left on device

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OSError: [Errno 28] No space left on device

I don’t think that Gradio error message was actually related to the crash.
It’s crashing due to lack of RAM or VRAM or HDD.
Maybe the model you are using is too big?

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this sometimes happen in zerogpu space if you restart the space several times due to some kind of caching mechanism, turn on the dev mode and open a terminal console, then rm -rf /data-nvme/zerogpu-offload/ and restart the space. it will work again. another way around is to make any modification on your source code in the repo, this will trigger a rebuild for the docker image of you space, after it’s fully restarted you will be fine.

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The error you’re encountering, OSError: [Errno 28] No space left on device, typically indicates that your system has run out of disk space. This happens when your application tries to allocate more storage (for example, while packing tensors) than is available on the device.

To resolve this, you can try the following steps:

  1. Check disk space: Verify the available disk space on your machine using commands like df -h in the terminal. If the disk is full, you need to free up space.
  2. Free up space:
  • Delete unnecessary files: Clear any unneeded files or logs on your machine.
  • Clear cache: If you’re using Hugging Face or similar frameworks, they may cache large models or data files. You can try clearing the cache, for example:

bash

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rm -rf ~/.cache/huggingface/
  • Remove old Docker images or containers (if you’re using Docker): Run docker system prune to remove unused images and containers.
  1. Increase disk space: If you cannot free up enough space, you might need to extend your disk or use a larger disk volume if possible.
  2. Check for excessive temporary files: Sometimes large temporary files can be generated during computation (like tensors). Investigate whether any such files exist and delete or move them.
  3. Upgrade Gradio: As mentioned in the warning, you’re using Gradio version 4.31.2 while version 5.0.1 is available. It might not directly affect disk space, but upgrading could resolve any compatibility or performance issues:

bash

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pip install --upgrade gradio
``If none of the above solves the issue, you might need to check with Hugging Face or the specific package causing the disk space issues to ensure it's not an underlying bug.