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Author:
Tushar Sarkar , Nishant Rajadhyaksha
License:
MIT
Summary:
TLA is built using PyTorch, Transformers and several other State-of-the-Art machine learning techniques and it aims to expedite and structure the cumbersome process of collecting, labeling, and analyzing data from Twitter for a corpus of languages while providing detailed labeled datasets for all the languages.
Latest version:
1.1
Required dependencies:
beautifulsoup4
|
certifi
|
charset-normalizer
|
click
|
colorama
|
cycler
|
filelock
|
huggingface-hub
|
idna
|
joblib
|
kiwisolver
|
lxml
|
matplotlib
|
nltk
|
numpy
|
packaging
|
pandas
|
pillow
|
pyparsing
|
pysocks
|
python-dateutil
|
pytz
|
pyyaml
|
regex
|
requests
|
sacremoses
|
scikit-learn
|
scipy
|
six
|
sklearn
|
snscrape
|
soupsieve
|
threadpoolctl
|
tokenizers
|
torch
|
tqdm
|
transformers
|
typing-extensions
|
urllib3
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