Python implementation of the Lox language from Robert Nystrom’s Crafting Interpreters. . This only implements the tree-walking interpreter in Part 1. Notes This is not a teaching exercise. I provide no commentary beyond the code itself and will likely implement using parser-generator tools. — Dave GitHub View Github    

wget https://repo.anaconda.com/archive/Anaconda3-5.2.0-Linux-x86_64.sh conda update -n base -c defaults conda conda create –name MCC python=3.6 source activate MCC conda install numpy pyyaml setuptools cmake cffi tqdm pyyaml scipy ipython mkl mkl-include cython typing h5py pandas nltk spacy numpydoc scikit-learn jpeg conda install pytorch==1.7.1 torchvision==0.8.2 cudatoolkit=11.0 -c pytorch    

This package provides spaCy components and architectures to use transformer models via Hugging Face’s transformers in spaCy. The result is convenient access to state-of-the-art transformer architectures, such as BERT, GPT-2, XLNet, etc. This release requires spaCy v3. For the previous version of this library, see the v0.6.x branch. Features Use pretrained transformer models like BERT, RoBERTa and XLNet to power your spaCy pipeline. Easy multi-task learning: backprop to one transformer model from several pipeline components. Train using spaCy v3’s powerful […]

GitHub – dredwardhyde/bert-ner-fine-tuning-cloud-deployment: Example Of Fine-Tuning BERT For Named-Entity Recognition Task And Preparing For Cloud Deployment Using Flask, React, And Docker Example Of Fine-Tuning BERT For Named-Entity Recognition Task And Preparing For Cloud Deployment Using Flask, React, And Docker – GitHub – dredwardhyde/bert-ner-fine-tuning-cloud-deployment: Exampl…    

VideoBERT This repo reproduces the results of VideoBERT (https://arxiv.org/pdf/1904.01766.pdf). Inspiration was taken from https://github.com/MDSKUL/MasterProject, but this repo tackles video prediction rather than captioning and masked language modeling. On a side note, since this model is extremely small, the results that are displayed here are extremely basic. Feel free to increase the model size per your computational resources and change the inference file to include temperature if necessary (As of now I have not implemented temperature). Here are all the steps […]

BERT-pytorch Pytorch implementation of Google AI’s 2018 BERT, with simple annotation BERT 2018 BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Paper URL : https://arxiv.org/abs/1810.04805 Google AI’s BERT paper shows the amazing result on various NLP task (new 17 NLP tasks SOTA),including outperform the human F1 score on SQuAD v1.1 QA task.This paper proved that Transformer(self-attention) based encoder can be powerfully used asalternative of previous language model with proper language model training method.And more importantly, they showed us that […]