instruction stringclasses 424
values | answer stringclasses 7
values | tag stringclasses 9
values | split_kind stringclasses 3
values | text stringclasses 424
values |
|---|---|---|---|---|
What type of text is this: The cat sat down. | prose | classify_prose | train_seen | Instruction: What type of text is this: The cat sat down.
Answer: prose <END> |
Classify this as positive or negative: I dislike this issue. | negative | sentiment_negative | train_seen | Instruction: Classify this as positive or negative: I dislike this issue.
Answer: negative <END> |
Classify input: This project needs more evidence. | prose | classify_prose | train_seen | Instruction: Classify input: This project needs more evidence.
Answer: prose <END> |
Make this professional: I can't make it. | I am unable to attend. | rewrite_professional_attend | tt639d_task_regression_carry_train | Instruction: Make this professional: I can't make it.
Answer: I am unable to attend. <END> |
Make this concise: I am going to be late today. | I will be late today. | rewrite_short_late | train_seen | Instruction: Make this concise: I am going to be late today.
Answer: I will be late today. <END> |
Classify this as positive or negative: This is awful. | negative | sentiment_negative | tt639f_failure_regression_train | Instruction: Classify this as positive or negative: This is awful.
Answer: negative <END> |
Choose the sentiment label for: I hate this bug. | negative | sentiment_negative | train_seen | Instruction: Choose the sentiment label for: I hate this bug.
Answer: negative <END> |
What sentiment is this: That failed again. | negative | sentiment_negative | tt639f_failure_regression_train | Instruction: What sentiment is this: That failed again.
Answer: negative <END> |
Label the sentiment: I like this result. | positive | sentiment_positive | train_seen | Instruction: Label the sentiment: I like this result.
Answer: positive <END> |
Classify sentiment: This is awful. | negative | sentiment_negative | train_seen | Instruction: Classify sentiment: This is awful.
Answer: negative <END> |
Is this sentiment positive or negative: The result is excellent. | positive | sentiment_positive | train_seen | Instruction: Is this sentiment positive or negative: The result is excellent.
Answer: positive <END> |
Type label: The cat sat down. | prose | classify_prose | train_seen | Instruction: Type label: The cat sat down.
Answer: prose <END> |
Choose one label, code or prose: def divide(a, b): return a / b | code | classify_code | train_seen | Instruction: Choose one label, code or prose: def divide(a, b): return a / b
Answer: code <END> |
Classify sentiment: I really like this. | positive | sentiment_positive | train_seen | Instruction: Classify sentiment: I really like this.
Answer: positive <END> |
What was Evan's meal today? | I don't know from the given information. | idk_food_today | train_seen | Instruction: What was Evan's meal today?
Answer: I don't know from the given information. <END> |
Classify sentiment: This is broken. | negative | sentiment_negative | tt639d_task_regression_carry_train | Instruction: Classify sentiment: This is broken.
Answer: negative <END> |
Choose the sentiment label for: This failed badly. | negative | sentiment_negative | train_seen | Instruction: Choose the sentiment label for: This failed badly.
Answer: negative <END> |
Give the sentiment label only: I like this result. | positive | sentiment_positive | train_seen | Instruction: Give the sentiment label only: I like this result.
Answer: positive <END> |
Label the input type: def add(a, b): return a + b | code | classify_code | tt639d_task_regression_carry_train | Instruction: Label the input type: def add(a, b): return a + b
Answer: code <END> |
Classify this as code or prose: def add(a, b): return a + b | code | classify_code | train_seen | Instruction: Classify this as code or prose: def add(a, b): return a + b
Answer: code <END> |
Classify input: The cat sat down. | prose | classify_prose | train_seen | Instruction: Classify input: The cat sat down.
Answer: prose <END> |
Label the sentiment: This is bad. | negative | sentiment_negative | train_seen | Instruction: Label the sentiment: This is bad.
Answer: negative <END> |
What sentiment is this: This is broken. | negative | sentiment_negative | train_seen | Instruction: What sentiment is this: This is broken.
Answer: negative <END> |
Is this code or prose: The user asked a direct question. | prose | classify_prose | train_seen | Instruction: Is this code or prose: The user asked a direct question.
Answer: prose <END> |
Classify sentiment: This is bad. | negative | sentiment_negative | train_seen | Instruction: Classify sentiment: This is bad.
Answer: negative <END> |
What type of text is this: A clear sky is usually blue. | prose | classify_prose | train_seen | Instruction: What type of text is this: A clear sky is usually blue.
Answer: prose <END> |
Make this concise: I am going to arrive late today. | I will be late today. | rewrite_short_late | train_seen | Instruction: Make this concise: I am going to arrive late today.
Answer: I will be late today. <END> |
Give only the type label for this: This sentence is plain English. | prose | classify_prose | train_seen | Instruction: Give only the type label for this: This sentence is plain English.
Answer: prose <END> |
What sentiment is this: This failed badly. | negative | sentiment_negative | train_seen | Instruction: What sentiment is this: This failed badly.
Answer: negative <END> |
Give only the type label for this: print('hello') | code | classify_code | train_seen | Instruction: Give only the type label for this: print('hello')
Answer: code <END> |
Give the sentiment label only: This is awful. | negative | sentiment_negative | train_seen | Instruction: Give the sentiment label only: This is awful.
Answer: negative <END> |
Classify this as positive or negative: That failed again. | negative | sentiment_negative | tt639f_failure_regression_train | Instruction: Classify this as positive or negative: That failed again.
Answer: negative <END> |
Make this concise: I am going to arrive late today. | I will be late today. | rewrite_short_late | train_seen | Instruction: Make this concise: I am going to arrive late today.
Answer: I will be late today. <END> |
Answer only positive or negative: This is awful. | negative | sentiment_negative | train_seen | Instruction: Answer only positive or negative: This is awful.
Answer: negative <END> |
Answer only code or prose: The appointment was moved to Friday. | prose | classify_prose | train_seen | Instruction: Answer only code or prose: The appointment was moved to Friday.
Answer: prose <END> |
What sentiment is this: This feels wrong. | negative | sentiment_negative | train_seen | Instruction: What sentiment is this: This feels wrong.
Answer: negative <END> |
What type of text is this: x = add(1, 2) | code | classify_code | tt639f_failure_regression_train | Instruction: What type of text is this: x = add(1, 2)
Answer: code <END> |
Label the sentiment: This is bad. | negative | sentiment_negative | train_seen | Instruction: Label the sentiment: This is bad.
Answer: negative <END> |
Label the sentiment: I am unhappy with this. | negative | sentiment_negative | train_seen | Instruction: Label the sentiment: I am unhappy with this.
Answer: negative <END> |
What was Evan's meal today? | I don't know from the given information. | idk_food_today | tt639d_task_regression_carry_train | Instruction: What was Evan's meal today?
Answer: I don't know from the given information. <END> |
Classify this as positive or negative: This is awful. | negative | sentiment_negative | train_seen | Instruction: Classify this as positive or negative: This is awful.
Answer: negative <END> |
Answer only code or prose: The appointment was moved to Friday. | prose | classify_prose | train_seen | Instruction: Answer only code or prose: The appointment was moved to Friday.
Answer: prose <END> |
Answer only positive or negative: I am unhappy with this. | negative | sentiment_negative | train_seen | Instruction: Answer only positive or negative: I am unhappy with this.
Answer: negative <END> |
What sentiment is this: This is awful. | negative | sentiment_negative | train_seen | Instruction: What sentiment is this: This is awful.
Answer: negative <END> |
Answer only positive or negative: This is good. | positive | sentiment_positive | train_seen | Instruction: Answer only positive or negative: This is good.
Answer: positive <END> |
Choose the sentiment label for: This is broken. | negative | sentiment_negative | train_seen | Instruction: Choose the sentiment label for: This is broken.
Answer: negative <END> |
Answer only positive or negative: This is good. | positive | sentiment_positive | train_seen | Instruction: Answer only positive or negative: This is good.
Answer: positive <END> |
What sentiment is this: That was helpful. | positive | sentiment_positive | train_seen | Instruction: What sentiment is this: That was helpful.
Answer: positive <END> |
Answer only code or prose: The appointment was moved to Friday. | prose | classify_prose | train_seen | Instruction: Answer only code or prose: The appointment was moved to Friday.
Answer: prose <END> |
Label the sentiment: I like this result. | positive | sentiment_positive | train_seen | Instruction: Label the sentiment: I like this result.
Answer: positive <END> |
Sentiment of this text: I really like this. | positive | sentiment_positive | train_seen | Instruction: Sentiment of this text: I really like this.
Answer: positive <END> |
Give the sentiment label only: This is bad. | negative | sentiment_negative | train_seen | Instruction: Give the sentiment label only: This is bad.
Answer: negative <END> |
Rewrite professionally: I can't make it. | I am unable to attend. | rewrite_professional_attend | tt639d_task_regression_carry_train | Instruction: Rewrite professionally: I can't make it.
Answer: I am unable to attend. <END> |
Is this code or prose: The meeting starts tomorrow. | prose | classify_prose | train_seen | Instruction: Is this code or prose: The meeting starts tomorrow.
Answer: prose <END> |
Classify this as positive or negative: This works great. | positive | sentiment_positive | train_seen | Instruction: Classify this as positive or negative: This works great.
Answer: positive <END> |
Is this sentiment positive or negative: This is awful. | negative | sentiment_negative | train_seen | Instruction: Is this sentiment positive or negative: This is awful.
Answer: negative <END> |
What sentiment is this: The result is terrible. | negative | sentiment_negative | train_seen | Instruction: What sentiment is this: The result is terrible.
Answer: negative <END> |
Label the sentiment: This failed badly. | negative | sentiment_negative | train_seen | Instruction: Label the sentiment: This failed badly.
Answer: negative <END> |
Polish this professionally: I won't be able to make it. | I am unable to attend. | rewrite_professional_attend | train_seen | Instruction: Polish this professionally: I won't be able to make it.
Answer: I am unable to attend. <END> |
Classify this as code or prose: This project needs more evidence. | prose | classify_prose | train_seen | Instruction: Classify this as code or prose: This project needs more evidence.
Answer: prose <END> |
Answer only code or prose: result = subtract(10, 5) | code | classify_code | train_seen | Instruction: Answer only code or prose: result = subtract(10, 5)
Answer: code <END> |
What sentiment is this: This is broken. | negative | sentiment_negative | train_seen | Instruction: What sentiment is this: This is broken.
Answer: negative <END> |
Choose one label, code or prose: The cat sat down. | prose | classify_prose | train_seen | Instruction: Choose one label, code or prose: The cat sat down.
Answer: prose <END> |
Label the sentiment: That was useful. | positive | sentiment_positive | train_seen | Instruction: Label the sentiment: That was useful.
Answer: positive <END> |
Classify input: A clear sky is usually blue. | prose | classify_prose | train_seen | Instruction: Classify input: A clear sky is usually blue.
Answer: prose <END> |
Choose the sentiment label for: I like this result. | positive | sentiment_positive | train_seen | Instruction: Choose the sentiment label for: I like this result.
Answer: positive <END> |
Label the input type: def add(a, b): return a + b | code | classify_code | train_seen | Instruction: Label the input type: def add(a, b): return a + b
Answer: code <END> |
Label the sentiment: I am unhappy with this. | negative | sentiment_negative | train_seen | Instruction: Label the sentiment: I am unhappy with this.
Answer: negative <END> |
Answer only code or prose: This sentence is plain English. | prose | classify_prose | train_seen | Instruction: Answer only code or prose: This sentence is plain English.
Answer: prose <END> |
What type of text is this: x = add(1, 2) | code | classify_code | tt639f_failure_regression_train | Instruction: What type of text is this: x = add(1, 2)
Answer: code <END> |
Is this sentiment positive or negative: This is broken. | negative | sentiment_negative | train_seen | Instruction: Is this sentiment positive or negative: This is broken.
Answer: negative <END> |
Give the sentiment label only: I dislike this issue. | negative | sentiment_negative | tt639f_failure_regression_train | Instruction: Give the sentiment label only: I dislike this issue.
Answer: negative <END> |
Answer only code or prose: class Tool: pass | code | classify_code | train_seen | Instruction: Answer only code or prose: class Tool: pass
Answer: code <END> |
Is this sentiment positive or negative: I hate this bug. | negative | sentiment_negative | train_seen | Instruction: Is this sentiment positive or negative: I hate this bug.
Answer: negative <END> |
Answer only positive or negative: I am unhappy with this. | negative | sentiment_negative | train_seen | Instruction: Answer only positive or negative: I am unhappy with this.
Answer: negative <END> |
Classify this as positive or negative: This failed badly. | negative | sentiment_negative | train_seen | Instruction: Classify this as positive or negative: This failed badly.
Answer: negative <END> |
Label the input type: for i in range(3): print(i) | code | classify_code | train_seen | Instruction: Label the input type: for i in range(3): print(i)
Answer: code <END> |
Classify sentiment: This is awful. | negative | sentiment_negative | train_seen | Instruction: Classify sentiment: This is awful.
Answer: negative <END> |
Classify this as positive or negative: That was useful. | positive | sentiment_positive | train_seen | Instruction: Classify this as positive or negative: That was useful.
Answer: positive <END> |
Choose one label, code or prose: This sentence is plain English. | prose | classify_prose | train_seen | Instruction: Choose one label, code or prose: This sentence is plain English.
Answer: prose <END> |
Give only the type label for this: y = multiply(3, 4) | code | classify_code | train_seen | Instruction: Give only the type label for this: y = multiply(3, 4)
Answer: code <END> |
Answer only code or prose: Please read the current file first. | prose | classify_prose | train_seen | Instruction: Answer only code or prose: Please read the current file first.
Answer: prose <END> |
Classify this as positive or negative: The result is terrible. | negative | sentiment_negative | train_seen | Instruction: Classify this as positive or negative: The result is terrible.
Answer: negative <END> |
Label the sentiment: This is bad. | negative | sentiment_negative | train_seen | Instruction: Label the sentiment: This is bad.
Answer: negative <END> |
What sentiment is this: This is awful. | negative | sentiment_negative | train_seen | Instruction: What sentiment is this: This is awful.
Answer: negative <END> |
Label the sentiment: This is broken. | negative | sentiment_negative | tt639d_task_regression_carry_train | Instruction: Label the sentiment: This is broken.
Answer: negative <END> |
Classify sentiment: This failed badly. | negative | sentiment_negative | train_seen | Instruction: Classify sentiment: This failed badly.
Answer: negative <END> |
Classify this as code or prose: The user asked a direct question. | prose | classify_prose | train_seen | Instruction: Classify this as code or prose: The user asked a direct question.
Answer: prose <END> |
Choose the sentiment label for: This is broken. | negative | sentiment_negative | train_seen | Instruction: Choose the sentiment label for: This is broken.
Answer: negative <END> |
Classify this as positive or negative: I dislike this issue. | negative | sentiment_negative | train_seen | Instruction: Classify this as positive or negative: I dislike this issue.
Answer: negative <END> |
Classify this as code or prose: The cat sat down. | prose | classify_prose | tt639d_task_regression_carry_train | Instruction: Classify this as code or prose: The cat sat down.
Answer: prose <END> |
Type label: result = subtract(10, 5) | code | classify_code | train_seen | Instruction: Type label: result = subtract(10, 5)
Answer: code <END> |
Is this sentiment positive or negative: This failed badly. | negative | sentiment_negative | train_seen | Instruction: Is this sentiment positive or negative: This failed badly.
Answer: negative <END> |
Classify input: result = subtract(10, 5) | code | classify_code | train_seen | Instruction: Classify input: result = subtract(10, 5)
Answer: code <END> |
What type of text is this: y = multiply(3, 4) | code | classify_code | train_seen | Instruction: What type of text is this: y = multiply(3, 4)
Answer: code <END> |
Do you have enough information to name my favorite movie? | I don't know from the given information. | idk_favorite_movie | train_seen | Instruction: Do you have enough information to name my favorite movie?
Answer: I don't know from the given information. <END> |
Is this sentiment positive or negative: This feels solid. | positive | sentiment_positive | train_seen | Instruction: Is this sentiment positive or negative: This feels solid.
Answer: positive <END> |
Give the sentiment label only: The output is poor. | negative | sentiment_negative | train_seen | Instruction: Give the sentiment label only: The output is poor.
Answer: negative <END> |
Choose one label, code or prose: A clear sky is usually blue. | prose | classify_prose | train_seen | Instruction: Choose one label, code or prose: A clear sky is usually blue.
Answer: prose <END> |
Label the input type: The dog ran home. | prose | classify_prose | train_seen | Instruction: Label the input type: The dog ran home.
Answer: prose <END> |
End of preview. Expand in Data Studio
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