An amateur attempts building the decoder block of transformer using PyTorch from scratch.
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Updated
Jun 2, 2024 - Python
An amateur attempts building the decoder block of transformer using PyTorch from scratch.
Deep Learning Course Assignment on Image Captioning and Machine Translation using LSTMs
Yet Another Transformer Implementation
The project aims to utilize pre-trained Large Language Models (LLMs) for text summarization through diverse fine-tuning techniques. Comparative analysis with baseline RNN/LSTM language models is undertaken, utilizing established metrics such as Rouge score and BLEU.
古诗生成模型,基于Transformer/Chinese poetry geneation, based on transformer.
Pytorch implementation of image captioning using transformer-based model.
An EncoderTransformer Architecture developed from scratch using pytorch's neural network module as the base class. The developed model used for sentiment analysis and time series prediction tasks.
Magic The GPT - GPT inspired model to generate Magic the Gathering cards
PyTorch implementation of the original transformer, from scratch
# 自然语言处理 IMDB 情感分析数据集任务
An encoder-transformer architecture-based framework for multi-variate time series prediction with a prognostics use case.
Pure C multi modal 3D Hybrid GAN using Cross attention, attention and convolution
A transformer-based model for automatic Image Captioning
A research project in vision-based deep reinforcement learning centered on transfer learning, unsupervised representation learning, and applying attention mechanisms to interpret memories.
Public repo for the paper: "COSMic: A Coherence-Aware Generation Metric for Image Descriptions" by Mert İnan, Piyush Sharma, Baber Khalid, Radu Soricut, Matthew Stone, Malihe Alikhani
pytorch Implementation of deep learning models
natural language processing with pytorch based on transformer model
Pronunciation correction in vector quantized PPG representation space
A Transformer Implementation that is easy to understand and customizable.
✨ Solve multi_dimensional multiple knapsack problem using state_of_the_art Reinforcement Learning Algorithms and transformers
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