Librarian Bot: Add base_model information to model

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  1. README.md +19 -24
README.md CHANGED
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  ---
 
 
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  license: apache-2.0
 
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  tags:
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  - generated_from_trainer
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  - chatgpt
 
 
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  metrics:
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  - accuracy
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- model-index:
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- - name: distilgpt2-HC3
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- results: []
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  widget:
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- - text: >-
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- Review: Best cast iron skillet you will ever buy. Is this review positive or
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- negative? <answer>
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  example_title: Sentiment analysis
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- - text: >-
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- Barack Obama nominated Hilary Clinton as his secretary of state on Monday.
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  He chose her because <answer>
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  example_title: Coreference resolution
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- - text: >-
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- On a shelf, there are five books: a gray book, a red book, a purple book, a
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- blue book, and a black book. Here's the puzzle, <answer>
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  example_title: Logic puzzles
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- - text: >-
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- The two men running to become New York City's next mayor will face off in
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  their first debate Wednesday night <answer>
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  example_title: Reading comprehension
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- - text: >-
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- Is it true that if I have five 5-hour energy drinks in a single 24-hour
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- period, I get 25 hours of energy and spontaneously explode? <answer>
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  example_title: 5 hour energy
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- - text: >-
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- what happens if you train a smaller model on a dataset of
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- reinforcement-learning optimized model responses? <answer>
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  example_title: deep learning advice
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  inference:
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  parameters:
@@ -39,12 +35,11 @@ inference:
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  max_length: 96
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  no_repeat_ngram_size: 3
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  repetition_penalty: 1.5
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- datasets:
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- - pszemraj/HC3-textgen-qa
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- language:
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- - en
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- library_name: transformers
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  pipeline_tag: text-generation
 
 
 
 
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  ---
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  ---
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+ language:
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+ - en
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  license: apache-2.0
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+ library_name: transformers
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  tags:
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  - generated_from_trainer
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  - chatgpt
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+ datasets:
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+ - pszemraj/HC3-textgen-qa
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  metrics:
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  - accuracy
 
 
 
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  widget:
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+ - text: 'Review: Best cast iron skillet you will ever buy. Is this review positive
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+ or negative? <answer>'
 
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  example_title: Sentiment analysis
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+ - text: Barack Obama nominated Hilary Clinton as his secretary of state on Monday.
 
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  He chose her because <answer>
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  example_title: Coreference resolution
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+ - text: 'On a shelf, there are five books: a gray book, a red book, a purple book,
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+ a blue book, and a black book. Here''s the puzzle, <answer>'
 
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  example_title: Logic puzzles
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+ - text: The two men running to become New York City's next mayor will face off in
 
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  their first debate Wednesday night <answer>
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  example_title: Reading comprehension
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+ - text: Is it true that if I have five 5-hour energy drinks in a single 24-hour period,
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+ I get 25 hours of energy and spontaneously explode? <answer>
 
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  example_title: 5 hour energy
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+ - text: what happens if you train a smaller model on a dataset of reinforcement-learning
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+ optimized model responses? <answer>
 
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  example_title: deep learning advice
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  inference:
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  parameters:
 
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  max_length: 96
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  no_repeat_ngram_size: 3
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  repetition_penalty: 1.5
 
 
 
 
 
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  pipeline_tag: text-generation
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+ base_model: distilgpt2
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+ model-index:
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+ - name: distilgpt2-HC3
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+ results: []
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  ---
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