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It's not the crux of this issue, but if the durarion designation exceeds 120 seconds, it's basically buggy.

It's not the crux of this issue, but if the durarion designation exceeds 120 seconds, it's basically buggy.

NO, I just do a test to find the quota.
Actually, the duration maybe 5~10s

Actually, the duration maybe 5~10s

Oh. If so, it's definitely a bug. 😅
I'm also using Zero GPU space, and sometimes the login quota doesn't work properly.
However, in my case, for some reason it's a different pattern from yours, and the login status doesn't work properly in the web browser. If I sign in explicitly using the OAuth sign-in button on the space, it works.
I've never used the Gradio Client...

I have exactly the same need as Nerva1228, and thanks John666 but it seems that, sound like a meme but, it's not a bug it's a feature. Not being able to use my PRO user quota programatically is not good, I want to test my own spaces with different combinations from within my code and I'm as limited as a normal user, is this intended to be that way or there is a solution, or maybe a feature for the future.

I got it to work!!!!

• I duplicated the black-forest-labs/FLUX.1-dev (!!!Important!!!! Go to their Model Card Page and get access granted to their gated model first. Then you can duplicate the model)
• Set the environment variables:
  HF_TOKEN =Use your HF_token (I used read and write credentials for this)
  ZEROGPU_V2=true
  ZERO_GPU_PATCH_TORCH_DEVICE=1

Then in your own (duplicated) space:

• Navigate to the Files
• Click on app.py
• Change

@spaces.GPU(duration=75)  # The duration max value can be 120 but this wasn't enough and still didn't work for me

to

@spaces.GPU()

Make sure in your python code that uses the gradio_client python library your HF_TOKEN is set in the environment or you set the parameter hf_token when creating the client
example:

from gradio_client import Client 
 client = CLIENT("your_duplicated_space/FLUX.1-dev", hf_token=os.getenv("HF_TOKEN"))

I got it to work!!!!

• I duplicated the black-forest-labs/FLUX.1-dev (!!!Important!!!! Go to their Model Card Page and get access granted to their gated model first. Then you can duplicate the model)
• Set the environment variables:
  HF_TOKEN =Use your HF_token (I used read and write credentials for this)
  ZEROGPU_V2=true
  ZERO_GPU_PATCH_TORCH_DEVICE=1

Then in your own (duplicated) space:

• Navigate to the Files
• Click on app.py
• Change

@spaces.GPU(duration=75)  # The duration max value can be 120 but this wasn't enough and still didn't work for me

to

@spaces.GPU()

Make sure in your python code that uses the gradio_client python library your HF_TOKEN is set in the environment or you set the parameter hf_token when creating the client
example:

from gradio_client import Client 
 client = CLIENT("your_duplicated_space/FLUX.1-dev", hf_token=os.getenv("HF_TOKEN"))

And what about the usage of the quota, you are able to use your PRO User quota??

I got it to work!!!!

• I duplicated the black-forest-labs/FLUX.1-dev (!!!Important!!!! Go to their Model Card Page and get access granted to their gated model first. Then you can duplicate the model)
• Set the environment variables:
  HF_TOKEN =Use your HF_token (I used read and write credentials for this)
  ZEROGPU_V2=true
  ZERO_GPU_PATCH_TORCH_DEVICE=1

Then in your own (duplicated) space:

• Navigate to the Files
• Click on app.py
• Change

@spaces.GPU(duration=75)  # The duration max value can be 120 but this wasn't enough and still didn't work for me

to

@spaces.GPU()

Make sure in your python code that uses the gradio_client python library your HF_TOKEN is set in the environment or you set the parameter hf_token when creating the client
example:

from gradio_client import Client 
 client = CLIENT("your_duplicated_space/FLUX.1-dev", hf_token=os.getenv("HF_TOKEN"))

And what about the usage of the quota, you are able to use your PRO User quota??

Yes. Try it out and see if it works for you.