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  • Dependency Conflict with huggingface-hub Version in Gradio and Llama . . .
    My application requires specific versions of libraries, especially huggingface-hub==0 23 5 and gradio==4 44 0, but a later step in my setup process unintentionally upgrades huggingface-hub, causing conflicts Here’s a breakdown of what I’ve tried and where the problem occurs:
  • Cant install gradio, tokenizers 0. 14. 1 requires huggingface-hub lt;0. 18 . . .
    This behaviour is the source of the following dependency conflicts tokenizers 0 14 1 requires huggingface-hub<0 18,>=0 16 4, but you have huggingface-hub 0 21 4 which is incompatible
  • gradio 5. 34. 2 - PyPI
    Gradio-Lite (@gradio lite): write Gradio apps in Python that run entirely in the browser (no server needed!), thanks to Pyodide Hugging Face Spaces : the most popular place to host Gradio applications — for free!
  • Installation - Hugging Face
    Before you start, you will need to setup your environment by installing the appropriate packages huggingface_hub is tested on Python 3 8+ It is highly recommended to install huggingface_hub in a virtual environment If you are unfamiliar with Python virtual environments, take a look at this guide
  • huggingface-hub 0. 0. 12 requires packaging gt;=20. 9, but youll have . . .
    You will have to update the huggingface-hub through pip install --upgrade huggingface-hub
  • Using Hugging Face Integrations - gradio. app
    Gradio has multiple features that make it extremely easy to leverage existing models and Spaces on the Hub This guide walks through these features Hugging Face has a service called Serverless Inference Endpoints, which allows you to send HTTP requests to models on the Hub
  • huggingface-hub 0. 33. 0 - PyPI
    The huggingface_hub library allows you to interact with the Hugging Face Hub, a platform democratizing open-source Machine Learning for creators and collaborators Discover pre-trained models and datasets for your projects or play with the thousands of machine learning apps hosted on the Hub
  • pydantic error occurs when passing gr. Dataframe #6297 - GitHub
    The error doesn't occur when using gradio==3 50 2 Running on local URL: http: 0 0 0 0:7860 To create a public link, set `share=True` in
  • Welcome, Gradio 5 - Hugging Face
    With Gradio 5, developers can build production-ready machine learning web applications that are performant, scalable, beautifully designed, accessible, and follow best web security practices, all in a few lines of Python To give Gradio 5 a spin, simply type in your terminal: pip install --upgrade gradio and start building your first
  • Gradio SDK 5. 31. 0 fully dysfunctional API on Huggingface
    What am I doing wrong? problem is, when I try to use a stable gradio like 4 44 or 5 8 in requirements txt, the HF environment always sets it back to the bug machine 5 31 0 Hmm… I think it’s just a bug It doesn’t seem to have been reported as an issue, though





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