25.1 hugging configure

ml configure hugging

Output will be something like:

*** The following required pip packages are already installed:

*** Installing Python package transformers by pip into

Do you want to pip install transformers [Y/n]? 
Collecting transformers
  Downloading transformers-4.22.1-py3-none-any.whl (4.9 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 4.9/4.9 MB 17.1 MB/s eta 0:00:00
Collecting requests
  Downloading requests-2.28.1-py3-none-any.whl (62 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 62.8/62.8 kB 11.4 MB/s eta 0:00:00


*** Installing Python package trafilatura by pip into

Do you want to pip install trafilatura [Y/n]? 
Collecting trafilatura
  Downloading trafilatura-1.3.0-py3-none-any.whl (1.0 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.0/1.0 MB 9.2 MB/s eta 0:00:00


*** Downloading required files ...

To view the model's README:

  $ ml readme hugging
  name         : hugging
  title        : implement various hugging face pipelines and models through MLHUB
  keywords     : python, summarization, transformers, t5, BART, sentiment-analysis
  version      : 0.0.2
  languages    : py
  license      : gpl3
  author       : Shashank Gummuluru
  url          : https://github.com/shashank-gv/summarize
    - torch
    - transformers
    - trafilatura
    - microsoft_text.txt
    - summarize.py
    - README.md
    - utils.py  
    - sentiment.py
    - sent_text.txt
    - demo.py
  summarize : Summarizes a given piece of text
  sentiment : Provides the sentiment ((pos | neg), score) of a given piece of text
  demo : Provides a demo of the commands implemented so far

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