Submit Hugging Face model links for quantization requests
Generate text responses using images and text prompts
Send queries and receive responses using Gemini models
Run AI web interface
Write your prompt and the AI will make it better!
Generate text based on input prompts
Generate text based on input prompts
Use AI to summarize, answer questions, translate, fill blanks, and paraphrase text
Login and Edit Projects with Croissant Editor
Display ranked leaderboard for models and RAG systems
Generate SQL queries from text descriptions
Generate text based on your input
Enhance Google Sheets with Hugging Face AI
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.