mustafaalisaba

mustafaalisaba's Stars

• facebookresearch/fairseq

  Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

  Language:Python30.7k4264.2k6.4k

• rasbt/deeplearning-models

  A collection of various deep learning architectures, models, and tips

  Language:Jupyter Notebook16.8k594304k

• fastai/numerical-linear-algebra

  Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course

  Language:Jupyter Notebook10.3k365172.6k

• yandexdataschool/nlp_course

  YSDA course in Natural Language Processing

  Language:Jupyter Notebook9.9k363462.6k

• nlp-with-transformers/notebooks

  Jupyter notebooks for the Natural Language Processing with Transformers book

  Language:Jupyter Notebook3.9k631011.2k

• rasbt/machine-learning-book

  Code Repository for Machine Learning with PyTorch and Scikit-Learn

  Language:Jupyter Notebook3.7k56971.4k

• fastai/course22

  The fast.ai course notebooks

  Language:Jupyter Notebook2.5k5273994

• aws-samples/aws-machine-learning-university-accelerated-nlp

  Machine Learning University: Accelerated Natural Language Processing Class

  Language:Jupyter Notebook2.4k1775611

• somosnlp/nlp-de-cero-a-cien

  Curso práctico: NLP de cero a cien 🤗

  Language:Jupyter Notebook18519289

• SAP-samples/acl2019-commonsense

  Source code for the paper "Attention Is (not) All You Need for Commonsense Reasoning" published at ACL 2019.

  Language:Python13767

• ptrichel/How-Reasonable-are-Common-Sense-Reasoning-Tasks

  Datasets to use the evaluation protocol for the Winograd Schema Challenge defined in the EMNLP2019 paper "How Reasonable are Common-Sense Reasoning Tasks: A Case-Study on the Winograd Schema Challenge and SWAG".

  5122

• hsjplus/high-level-kb-reasoning

  Language:Jupyter Notebook4101