error failed building wheel for httptools

While installing latest version of RASA have faced the following issue

Solution: conda install -c conda-forge httptools

Generate Text using OpenAIGPT2 in Python

!git clone https://github.com/graykode/gpt-2-Pytorch
import os
os.chdir('gpt-2-Pytorch')
!curl --output gpt2-pytorch_model.bin https://s3.amazonaws.com/models.huggingface.co/bert/gpt2-pytorch_model.bin
!pip install -r requirements.txt
!python main.py --text "Chandrayaan-2 is India's second lunar exploration mission after Chandrayaan-1. Developed by the Indian Space Research Organisation, the mission was launched from the second launch pad at Satish Dhawan Space Centre on 22 July 2019 at 2.43 PM IST to the Moon by a Geosynchronous Satellite Launch Vehicle Mark III."

Free GPU, TPU on Google Colab

Happy learning and experiments with Google Colab

Note: Data might be lost after 12hrs
We can run the tensorboard on colab too.
Reference links
Google SEEDBANK
https://research.google.com/seedbank/seeds?keyword=text
https://colab.research.google.com/

Question-Answering system with cdQA-suite

This is Transfer Learning era on NLP tasks.
Have been working on how to use my data set on XLNet and BERT.
Found excellent references with community help

https://towardsdatascience.com/how-to-create-your-own-question-answering-system-easily-with-python-2ef8abc8eb5
https://github.com/cdqa-suite/cdQA

XLNet - A SOTA model

While working on the Q&A system, have found pretrained model on NLP. XLNET is state of the art model for Q&A applications.
XLNet is the combination of Autoregressive  and autoencoding

Generalized Autoregressive Pretraining for Language Understanding.

Generalized -- Pretrain without data correption( masking) by using permutation LM.

Auto regressive – Autoregressive language model but also utilizes bidirectional context

This is better than BERT

References:
https://arxiv.org/abs/1906.08237
https://mlexplained.com/2019/06/30/paper-dissected-xlnet-generalized-autoregressive-pretraining-for-language-understanding-explained/