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Model Benchmarking
Push Model From Web

Push Model From Web

Upload ML model to Hugging Face Hub

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What is Push Model From Web ?

Push Model From Web is a tool designed for model benchmarking, enabling users to easily upload and manage machine learning models directly to the Hugging Face Hub. It simplifies the process of deploying and evaluating ML models, making it accessible for developers and researchers alike. The tool supports various machine learning frameworks and model types, providing a seamless experience for model sharing and collaboration.

Features

• Model Deployment: Directly upload your machine learning model to Hugging Face Hub for easy access and sharing.
• Framework Support: Compatible with popular frameworks such as TensorFlow, PyTorch, and more.
• Model Benchmarking: Compare performance metrics of different models in a centralized environment.
• Community Integration: Share models with the broader machine learning community for feedback and collaboration.
• Version Control: Track different versions of your model for iterative development and testing.

How to use Push Model From Web ?

  1. Access the Tool: Navigate to the Push Model From Web interface through your preferred browser.
  2. Prepare Your Model: Ensure your machine learning model is packaged in a supported format (e.g., .h5, .pth, .onnx).
  3. Upload Your Model: Use the intuitive interface to select and upload your model file.
  4. Configure Settings: Provide metadata such as model name, description, and tags for better organization.
  5. Review Metrics: Once uploaded, review benchmarking metrics and performance data.
  6. Share Your Model: Publish your model to the Hugging Face Hub for public or private access.

Frequently Asked Questions

1. What is the primary purpose of Push Model From Web?
The primary purpose is to simplify the deployment and sharing of machine learning models to the Hugging Face Hub, enabling benchmarking and collaboration.

2. Which machine learning frameworks are supported?
Push Model From Web supports models from popular frameworks like TensorFlow, PyTorch, and others, ensuring compatibility with a wide range of ML workflows.

3. Where are the uploaded models stored?
Uploaded models are stored on the Hugging Face Hub, a cloud-based platform designed for sharing and managing machine learning models.

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