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--- |
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license: mit |
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language: |
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- en |
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widget: |
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- text: >- |
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A nervous passenger is about to book a flight ticket, and he asks the |
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airlines' ticket seller, 'I hope your planes are safe. Do they have a good |
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track record for safety?' The airline agent replies, 'Sir, I can guarantee |
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you, we've never had a plane that has crashed more than once.' |
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example_title: A joke |
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- text: >- |
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Let me, however, hasten to assure that I am the same Gandhi as I was in |
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1920. I have not changed in any fundamental respect. I attach the same |
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importance to nonviolence that I did then. If at all, my emphasis on it has |
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grown stronger. There is no real contradiction between the present |
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resolution and my previous writings and utterances. |
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example_title: Not a joke |
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tags: |
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- distilbert |
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--- |
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### What is this? |
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This model has been developed to detect "narrative-style" jokes, stories and anecdotes (i.e. they are narrated as a story) spoken during speeches or conversations etc. It works best when jokes/anecdotes are at least 40 words or longer. It is based on [lvwerra's distilbert](https://huggingface.co/lvwerra/distilbert-imdb). |
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The training dataset was a private collection of around 2000 jokes. This model has not been trained or tested on one-liners, puns or Reddit-style language-manipulation jokes such as knock-knock, Q&A jokes etc. |
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See the example in the inference widget or How to use section for what constitues a narrative-style joke. |
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For a more accurate model (2.4% more) that is slower at inference, see the [Roberta model](https://huggingface.co/Reggie/muppet-roberta-base-joke_detector). For a still more accurate model (2.9% more) that is much slower at inference, see the [Deberta-v3 model](https://huggingface.co/Reggie/DeBERTa-v3-base-joke_detector). |
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### Install these first |
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You'll need to pip install transformers & maybe sentencepiece |
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### How to use |
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```python |
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from transformers import pipeline |
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import torch |
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device = 0 if torch.cuda.is_available() else -1 |
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model_name = 'Reggie/distilbert-joke_detector' |
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max_seq_len = 510 |
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pipe = pipeline(model=model_name, device=device, truncation=True, max_length=max_seq_len) |
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is_it_a_joke = """A nervous passenger is about to book a flight ticket, and he asks the airlines' ticket seller, "I hope your planes are safe. Do they have a good track record for safety?" The airline agent replies, "Sir, I can guarantee you, we've never had a plane that has crashed more than once." """ |
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result = pipe(is_it_a_joke) # [{'label': 'POSITIVE', 'score': 0.7313136458396912}] |
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print('This is a joke') if result[0]['label'] == 'POSITIVE' else print('This is not a joke') |
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``` |
