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Browse files- README.md +4 -4
- requirements.txt +1 -1
- single.py +4 -4
README.md
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---
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title:
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emoji:
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sdk: streamlit
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sdk_version: 1.10.0
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app_file: app.py
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title: ferret
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emoji: π¦‘
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colorFrom: blue
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colorTo: purple
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sdk: streamlit
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sdk_version: 1.10.0
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app_file: app.py
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requirements.txt
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transformers==4.20.1
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ferret-xai==0.3.
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sentencepiece
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transformers==4.20.1
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ferret-xai==0.3.1
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sentencepiece
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single.py
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You are working now on the *single instance* mode -- i.e., you will work and
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inspect one textual query at a time.
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Post-hoc explanation techniques
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makes while detecting a sentiment out of a text. In a sense
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But **who watches the watchers**?
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Let's find out!
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Let's choose your favourite
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We will:
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1. download your model - if you're impatient, here it is a [cute video](https://www.youtube.com/watch?v=0Xks8t-SWHU) π¦ for you;
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You are working now on the *single instance* mode -- i.e., you will work and
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inspect one textual query at a time.
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Post-hoc explanation techniques disclose π the rationale behind a given prediction a model
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makes while detecting a sentiment out of a text. In a sense, they let you *poke* inside the model.
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But **who watches the watchers**? Are these explanations *accurate*? Can you *trust* them?
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Let's find out!
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Let's choose your favourite mode and let *ferret* do the rest.
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We will:
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1. download your model - if you're impatient, here it is a [cute video](https://www.youtube.com/watch?v=0Xks8t-SWHU) π¦ for you;
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