The Encoder-Decoder architecture is widely used in sequence-to-sequence tasks such as machine translation, text summarization, and speech recognition. However, traditional Encoder-Decoder models face ...

This project implements an Image-to-Text Model using an encoder-decoder architecture. The model takes an input image, encodes it into a feature vector using a pre-trained ResNet50, ... Experiment with ...

Speech enhancement (SE) models based on deep neural networks (DNNs) have shown excellent denoising performance. However, mainstream SE models often have high structural complexity and large parameter ...

Encoder-Decoder Architecture. Based on the vanilla Transformer model, the encoder-decoder architecture consists of two stacks: an encoder and a decoder. The encoder uses stacked multi-head ...

Tech giant Microsoft (MSFT) has launched a new small language model called Mu that is built to handle complex language tasks efficiently on devices like Copilot+ PCs. Unlike larger AI models that run ...

The 330 million parameter model was trained using Azure’s A100 GPUs and fine-tuned through a multi-phase process.