Submit Hugging Face model links for quantization requests
Generate text prompts for creative projects
Generate test cases from a QA user story
Generate and edit content
Transcribe audio or YouTube videos
Multi-Agent AI with crewAI
Generate text with input prompts
Optimum CLI Commands. Compress, Quantize and Convert!
Online demo of paper: Chain of Ideas: Revolutionizing Resear
Generate detailed script for podcast or lecture from text input
Chat with an Italian Small Model
Create and run Jupyter notebooks interactively
Generate optimized prompts for Stable Diffusion
Quant Request is a web application designed to facilitate the quantization of machine learning models, particularly those hosted on Hugging Face. It allows users to submit model links for the quantization process, making it easier to optimize models for inference and deployment.
• Model Quantization: Enables users to convert floating-point models into quantized versions for better performance and efficiency.
• Hugging Face Model Support: Directly accepts model links from the Hugging Face ecosystem for seamless integration.
• Optimized for Inference: Helps reduce model size and improve speed, ideal for resource-constrained environments.
• User-Friendly Interface: Simplifies the quantization process with minimal user input required.
What models are supported by Quant Request?
Quant Request supports models available on the Hugging Face Model Hub. It is compatible with models in the ONNX or PyTorch format.
Is model quantization reversible?
No, quantization is an irreversible process. Once a model is quantized, it cannot be converted back to its original floating-point precision without loss.
Where can I find Hugging Face model links?
You can explore and find Hugging Face models on the Hugging Face Model Hub. Simply copy the model's URL and submit it to Quant Request.