Evaluation code for various unsupervised automated metrics for Natural Language Generation.
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Updated
Jun 24, 2024 - Python
Evaluation code for various unsupervised automated metrics for Natural Language Generation.
A neural network to generate captions for an image using CNN and RNN with BEAM Search.
A modular library built on top of Keras and TensorFlow to generate a caption in natural language for any input image.
Python code for various NLP metrics
The LSTM model generates captions for the input images after extracting features from pre-trained VGG-16 model. (Computer Vision, NLP, Deep Learning, Python)
A basic AI chat using the OpenAI API and its GPT-3 models
Useful python NLP tools (evaluation, GUI interface, tokenization)
A visual and interactive scoring environment for machine translation systems.
Deep CNN-LSTM for Generating Image Descriptions 😈
To evaluate machine translation, they use several methods, some of which we fully implemented
Scripts for an upcoming blog "Extractive vs. Abstractive Summarization" for RaRe Technologies.
State of the art of Neural Machine Translation with PyTorch and TorchText.
In this project, I define and train an image-to-caption model that can produce descriptions for real world images with Flickr-8k dataset.
Implementation for paper BLEU: a Method for Automatic Evaluation of Machine Translation
⚡ Seq2Seq model combines Attention mechanism
Machine learning tools for NLP programming.
Generate caption on images using CNN Encoder- LSTM Decoder structure
Repository containing the code to my bachelor thesis about Neural Machine Translation
Tensorflow implementation of "Show and Tell"
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