# RuTurboAlpaca

Dataset of ChatGPT-generated instructions in Russian.


<img src="https://cdn.midjourney.com/770a35fa-00c0-4214-bb88-727dbc7cfaf3/0_0.png" >

* Code: [rulm/self_instruct](https://github.com/IlyaGusev/rulm/tree/master/self_instruct)
* Code is based on [Stanford Alpaca](https://github.com/tatsu-lab/stanford_alpaca) and [self-instruct](https://github.com/yizhongw/self-instruct/).
* 29822 examples

Preliminary evaluation by an expert based on 400 samples:
* 83% of samples contain correct instructions
* 63% of samples have correct instructions and outputs

Crowdsouring-based evaluation on 3500 samples:
* 90% of samples contain correct instructions
* 68% of samples have correct instructions and outputs

Prompt template:
```
Составь набор из {{num_tasks}} разных заданий для дообучения языковой модели:

1. Делай задания максимально непохожими друг на друга: по типу, по запрашиваемым действиям, по формулировке, по наличию входа.
2. Задания должны быть выполнимы языковой моделью, которая не умеет работать с картинками, видео, и аудио, и не имеет доступа ко внешнему миру.
3. Используй хороший грамотный русский язык.
4. Делай задания в одно или два предложения.
5. Генерируй подходящие реалистичные входные данные, не используй общие шаблоны типа \"Имя человека\" или [имя] вместо реального имени.
6. Задание может быть без входных данных, в таком случае используй токен <noinput> вместо них.
7. На выходе сгенерируй подходящий длинный ответ.
8. Следуй тому же шаблону, который приведен в примерах, разделяй задания с помощью ###. Это важно!

Примеры заданий:
{% for task in example_tasks %}
{{task.index}}. Задание: {{task.instruction}}
{{task.index}}. Вход: {{task.input}}
{{task.index}}. Выход: {{task.output}}

{{ "###" if not loop.last else "" }}
{% endfor %}
```


## Legal disclaimer

Data is based on OpenAI’s gpt-3.5-turbo, whose [terms of use](https://openai.com/policies/terms-of-use) prohibit for us developing models that compete with OpenAI. Not for you.
task_categories:text-generation task_categories:text2text-generation size_categories:10K<n<100K language:ru license:cc-by-4.0 instruction-finetuning instruction generation alpaca region:us
{"language": ["ru"], "license": "cc-by-4.0", "size_categories": ["10K<n<100K"], "task_categories": ["text-generation", "text2text-generation"], "dataset_info": {"features": [{"name": "instruction", "dtype": "string"}, {"name": "input", "dtype": "string"}, {"name": "output", "dtype": "string"}, {"name": "alternative_output", "dtype": "string"}, {"name": "label", "dtype": "string"}, {"name": "all_labels", "sequence": "string"}, {"name": "agreement", "dtype": "float32"}, {"name": "overlap", "dtype": "uint32"}], "splits": [{"name": "train", "num_bytes": 54774775, "num_examples": 29822}], "download_size": 14565995, "dataset_size": 54774775}, "tags": ["instruction-finetuning", "instruction generation", "alpaca"]}
TAGS
#task_categories-text-generation #task_categories-text2text-generation #size_categories-10K<n<100K #language-Russian #license-cc-by-4.0 #instruction-finetuning #instruction generation #alpaca #region-us 

# RuTurboAlpaca

Dataset of ChatGPT-generated instructions in Russian.


<img src="URL >

* Code: rulm/self_instruct
* Code is based on Stanford Alpaca and self-instruct.
* 29822 examples

Preliminary evaluation by an expert based on 400 samples:
* 83% of samples contain correct instructions
* 63% of samples have correct instructions and outputs

Crowdsouring-based evaluation on 3500 samples:
* 90% of samples contain correct instructions
* 68% of samples have correct instructions and outputs

Prompt template:



## Legal disclaimer

Data is based on OpenAI’s gpt-3.5-turbo, whose terms of use prohibit for us developing models that compete with OpenAI. Not for you.
# RuTurboAlpaca

Dataset of ChatGPT-generated instructions in Russian.


<img src="URL >

* Code: rulm/self_instruct
* Code is based on Stanford Alpaca and self-instruct.
* 29822 examples

Preliminary evaluation by an expert based on 400 samples:
* 83% of samples contain correct instructions
* 63% of samples have correct instructions and outputs

Crowdsouring-based evaluation on 3500 samples:
* 90% of samples contain correct instructions
* 68% of samples have correct instructions and outputs

Prompt template: ## Legal disclaimer

Data is based on OpenAI’s gpt-3.5-turbo, whose terms of use prohibit for us developing models that compete with OpenAI. Not for you.
TAGS
#task_categories-text-generation #task_categories-text2text-generation #size_categories-10K<n<100K #language-Russian #license-cc-by-4.0 #instruction-finetuning #instruction generation #alpaca #region-us 
 # RuTurboAlpaca

Dataset of ChatGPT-generated instructions in Russian.


<img src="URL >

* Code: rulm/self_instruct
* Code is based on Stanford Alpaca and self-instruct.
* 29822 examples

Preliminary evaluation by an expert based on 400 samples:
* 83% of samples contain correct instructions
* 63% of samples have correct instructions and outputs

Crowdsouring-based evaluation on 3500 samples:
* 90% of samples contain correct instructions
* 68% of samples have correct instructions and outputs

Prompt template: ## Legal disclaimer

Data is based on OpenAI’s gpt-3.5-turbo, whose terms of use prohibit for us developing models that compete with OpenAI. Not for you.
passage: TAGS
#task_categories-text-generation #task_categories-text2text-generation #size_categories-10K<n<100K #language-Russian #license-cc-by-4.0 #instruction-finetuning #instruction generation #alpaca #region-us 
# RuTurboAlpaca

Dataset of ChatGPT-generated instructions in Russian.


<img src="URL >

* Code: rulm/self_instruct
* Code is based on Stanford Alpaca and self-instruct.
* 29822 examples

Preliminary evaluation by an expert based on 400 samples:
* 83% of samples contain correct instructions
* 63% of samples have correct instructions and outputs

Crowdsouring-based evaluation on 3500 samples:
* 90% of samples contain correct instructions
* 68% of samples have correct instructions and outputs

Prompt template:## Legal disclaimer

Data is based on OpenAI’s gpt-3.5-turbo, whose terms of use prohibit for us developing models that compete with OpenAI. Not for you.