[Python] I have a meta-3b-instruct auth error error while executing my webapp on streamlit...

Discussão em 'Python' iniciado por Stack, Dezembro 7, 2024.

  1. Stack

    Stack Membro Participativo

    I have been building a app in streamlit cloud which uses github repo to execute code. Now i am using a hugging face model in the code. I have API key and permission granted for meta-3b-Instruct and 8b-instruct.When i execute the app on streamlit cloud it shows this error

    OSError: You are trying to access a gated repo. Make sure to have access to it at https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct. 401 Client Error. (Request ID: Root=1-67548f30-095cd98c1ddbd00c71f600a7;c0521d6a-9a16-4df8-a8b0-bffe17427f8e) Cannot access gated repo for url https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct/resolve/main/config.json Access to model meta-llama/Llama-3.2-3B-Instruct is restricted. You must have access to it and be authenticated to access it. Please log in. 2024-12-07 18:08:50.428 Examining the path of torch.classes raised: Tried to instantiate class 'path.path', but it does not exist! Ensure that it is registered via torch::class

    Below is my code, I m using LIDA library to build a data analysis app.


    text_gen = llm(
    provider="hf",
    model="meta-llama/Llama-3.2-3B-Instruct",
    api_key=hf_api_key,
    device_map="auto"
    )
    lida = Manager(text_gen=text_gen)

    textgen_config = TextGenerationConfig(
    n=1,
    temperature=0,
    model="meta-llama/Llama-3.2-3B-Instruct",
    use_cache=use_cache
    )

    st.write("## Summary")`


    Need help to overcome this issue the ID is active and i have the been granted the permission to use above meta models on hugging face.

    Also i have another question, how much i have got on streamlit cloud to execute my model. If the above problem is solved i dont know which model i can download.Will anyone be needing to download model everytime they access this website ?

    I m expecting how to overcome this issue and also which model I can use which will best fit for the space available on streamlit cloud and github.

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