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Quant Request is a tool designed to facilitate the quantization of AI models. It allows users to submit Hugging Face model links for quantization requests, enabling the optimization of models for improved performance and efficiency. Quantization is a process that reduces the size and computational requirements of AI models while maintaining their functionality, making them more suitable for deployment in resource-constrained environments.
• Model Optimization: Simplify the process of optimizing AI models for inference.
• Hugging Face Integration: Directly submit model links from the Hugging Face ecosystem.
• Customizable Options: Tailor the quantization process to meet specific requirements.
• Efficiency Boost: Reduce model size and improve performance for faster execution.
What models are supported by Quant Request?
Quant Request supports models available on the Hugging Face Model Hub, with a focus on popular architectures like BERT, ResNet, and other widely-used frameworks.
How long does the quantization process take?
The duration depends on the model size and complexity. Typically, smaller models are processed within minutes, while larger models may require additional time.
What formats are supported for output?
Quant Request outputs models in standardized formats such as ONNX and TensorFlow Lite, ensuring compatibility with various deployment environments.