

# Dataset Card for words-operations-rewards-5k with 5K entries.

### Dataset Summary

License: Apache-2.0. Contains JSONL. Use this for Reward Models.

# Solved tasks:

- Count Letters;
- Write Backwards;
- Write Character on a Position;
- Repeat Word;
- Write In Case;
- Change Case on a Position;
- Write Numbering;
- Connect Characters;
- Write a Word from Characters;
- Count Syllables;

# Example:

```json
{
  "message_tree_id": "00000000-0000-0000-0000-000000000004",
  "tree_state": "ready_for_export",
  "prompt": {
    "message_id": "00000000-0000-0000-0000-000000000004",
    "text": "Count the number of letters in the word «detailed»",
    "role": "prompter",
    "lang": "en",
      "replies": [
        { "message_id": "00000000-0000-0000-0000-000000000005",
           "text": "8", "role": "assistant", "lang": "en",
           "meta": {"rank": 1}, "replies": []},
        { "message_id": "00000000-0000-0000-0000-000000000006",
            "text": "7", "role": "assistant", "lang": "en",
            "meta": {"rank": 0}, "replies": []},
       {"message_id": "00000000-0000-0000-0000-000000000007",
           "text": "7 or 9", "role": "assistant", "lang": "en",
           "meta": {"rank": 0}, "replies": []}]
    }
}
```
task_categories:text-classification task_categories:token-classification task_categories:question-answering size_categories:1K<n<10K language:en language:ru license:apache-2.0 semantics region:us
{"language": ["en", "ru"], "license": "apache-2.0", "size_categories": ["1K<n<10K"], "task_categories": ["text-classification", "token-classification", "question-answering"], "tags": ["semantics"]}
TAGS
#task_categories-text-classification #task_categories-token-classification #task_categories-question-answering #size_categories-1K<n<10K #language-English #language-Russian #license-apache-2.0 #semantics #region-us 



# Dataset Card for words-operations-rewards-5k with 5K entries.

### Dataset Summary

License: Apache-2.0. Contains JSONL. Use this for Reward Models.

# Solved tasks:

- Count Letters;
- Write Backwards;
- Write Character on a Position;
- Repeat Word;
- Write In Case;
- Change Case on a Position;
- Write Numbering;
- Connect Characters;
- Write a Word from Characters;
- Count Syllables;

# Example:


# Dataset Card for words-operations-rewards-5k with 5K entries. ### Dataset Summary

License: Apache-2.0. Contains JSONL. Use this for Reward Models. # Solved tasks:

- Count Letters;
- Write Backwards;
- Write Character on a Position;
- Repeat Word;
- Write In Case;
- Change Case on a Position;
- Write Numbering;
- Connect Characters;
- Write a Word from Characters;
- Count Syllables; # Example:
TAGS
#task_categories-text-classification #task_categories-token-classification #task_categories-question-answering #size_categories-1K<n<10K #language-English #language-Russian #license-apache-2.0 #semantics #region-us 
 # Dataset Card for words-operations-rewards-5k with 5K entries. ### Dataset Summary

License: Apache-2.0. Contains JSONL. Use this for Reward Models. # Solved tasks:

- Count Letters;
- Write Backwards;
- Write Character on a Position;
- Repeat Word;
- Write In Case;
- Change Case on a Position;
- Write Numbering;
- Connect Characters;
- Write a Word from Characters;
- Count Syllables; # Example:
passage: TAGS
#task_categories-text-classification #task_categories-token-classification #task_categories-question-answering #size_categories-1K<n<10K #language-English #language-Russian #license-apache-2.0 #semantics #region-us 
# Dataset Card for words-operations-rewards-5k with 5K entries.### Dataset Summary

License: Apache-2.0. Contains JSONL. Use this for Reward Models.# Solved tasks:

- Count Letters;
- Write Backwards;
- Write Character on a Position;
- Repeat Word;
- Write In Case;
- Change Case on a Position;
- Write Numbering;
- Connect Characters;
- Write a Word from Characters;
- Count Syllables;# Example: