@@ -12,29 +12,29 @@ const inputsSummarization = () =>
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const inputsTableQuestionAnswering = ( ) =>
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`{
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- "query": "How many stars does the transformers repository have?",
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- "table": {
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- "Repository": ["Transformers", "Datasets", "Tokenizers"],
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- "Stars": ["36542", "4512", "3934"],
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- "Contributors": ["651", "77", "34"],
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- "Programming language": [
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- "Python",
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- "Python",
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- "Rust, Python and NodeJS"
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- ]
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- }
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+ "query": "How many stars does the transformers repository have?",
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+ "table": {
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+ "Repository": ["Transformers", "Datasets", "Tokenizers"],
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+ "Stars": ["36542", "4512", "3934"],
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+ "Contributors": ["651", "77", "34"],
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+ "Programming language": [
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+ "Python",
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+ "Python",
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+ "Rust, Python and NodeJS"
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+ ]
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+ }
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}` ;
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const inputsVisualQuestionAnswering = ( ) =>
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`{
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- "image": "cat.png",
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- "question": "What is in this image?"
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- }`;
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+ "image": "cat.png",
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+ "question": "What is in this image?"
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+ }`;
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const inputsQuestionAnswering = ( ) =>
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`{
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- "question": "What is my name?",
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- "context": "My name is Clara and I live in Berkeley."
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+ "question": "What is my name?",
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+ "context": "My name is Clara and I live in Berkeley."
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}` ;
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const inputsTextClassification = ( ) => `"I like you. I love you"` ;
@@ -72,12 +72,12 @@ const inputsFillMask = (model: ModelDataMinimal) => `"The answer to the universe
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const inputsSentenceSimilarity = ( ) =>
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`{
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- "source_sentence": "That is a happy person",
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- "sentences": [
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- "That is a happy dog",
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- "That is a very happy person",
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- "Today is a sunny day"
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- ]
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+ "source_sentence": "That is a happy person",
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+ "sentences": [
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+ "That is a happy dog",
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+ "That is a very happy person",
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+ "Today is a sunny day"
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+ ]
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}` ;
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const inputsFeatureExtraction = ( ) => `"Today is a sunny day and I will get some ice cream."` ;
@@ -87,8 +87,8 @@ const inputsImageClassification = () => `"cats.jpg"`;
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const inputsImageToText = ( ) => `"cats.jpg"` ;
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const inputsImageToImage = ( ) => `{
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- "image": "cat.png",
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- "prompt": "Turn the cat into a tiger."
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+ "image": "cat.png",
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+ "prompt": "Turn the cat into a tiger."
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}` ;
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const inputsImageSegmentation = ( ) => `"cats.jpg"` ;
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