# Sequential Instructions

This is the sequential instructions dataset from [Understanding the Effects of RLHF on LLM Generalisation and Diversity](https://arxiv.org/abs/2310.06452). The dataset is in the `alpaca_eval` format.

For information about how the dataset was generated, see https://github.com/RobertKirk/stanford_alpaca.

The instructions in the dataset generally have a sequence of steps we expect the model to complete all at once. In our work, we found that RLHF models generalise much better to this dataset than SFT models when trained on the AlpacaFarm datasets.
task_categories:question-answering task_categories:text-generation size_categories:n<1K language:en license:mit arxiv:2310.06452 region:us
{"language": ["en"], "license": "mit", "size_categories": ["n<1K"], "task_categories": ["question-answering", "text-generation"], "pretty_name": "Sequential Instructions", "dataset_info": {"features": [{"name": "dataset", "dtype": "string"}, {"name": "instruction", "dtype": "string"}, {"name": "output", "dtype": "string"}, {"name": "generator", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 736696, "num_examples": 533}], "download_size": 373739, "dataset_size": 736696}}
TAGS
#task_categories-question-answering #task_categories-text-generation #size_categories-n<1K #language-English #license-mit #arxiv-2310.06452 #region-us 

# Sequential Instructions

This is the sequential instructions dataset from Understanding the Effects of RLHF on LLM Generalisation and Diversity. The dataset is in the 'alpaca_eval' format.

For information about how the dataset was generated, see URL

The instructions in the dataset generally have a sequence of steps we expect the model to complete all at once. In our work, we found that RLHF models generalise much better to this dataset than SFT models when trained on the AlpacaFarm datasets.
# Sequential Instructions

This is the sequential instructions dataset from Understanding the Effects of RLHF on LLM Generalisation and Diversity. The dataset is in the 'alpaca_eval' format.

For information about how the dataset was generated, see URL

The instructions in the dataset generally have a sequence of steps we expect the model to complete all at once. In our work, we found that RLHF models generalise much better to this dataset than SFT models when trained on the AlpacaFarm datasets.
TAGS
#task_categories-question-answering #task_categories-text-generation #size_categories-n<1K #language-English #license-mit #arxiv-2310.06452 #region-us 
 # Sequential Instructions

This is the sequential instructions dataset from Understanding the Effects of RLHF on LLM Generalisation and Diversity. The dataset is in the 'alpaca_eval' format.

For information about how the dataset was generated, see URL

The instructions in the dataset generally have a sequence of steps we expect the model to complete all at once. In our work, we found that RLHF models generalise much better to this dataset than SFT models when trained on the AlpacaFarm datasets.
passage: TAGS
#task_categories-question-answering #task_categories-text-generation #size_categories-n<1K #language-English #license-mit #arxiv-2310.06452 #region-us 
# Sequential Instructions

This is the sequential instructions dataset from Understanding the Effects of RLHF on LLM Generalisation and Diversity. The dataset is in the 'alpaca_eval' format.

For information about how the dataset was generated, see URL

The instructions in the dataset generally have a sequence of steps we expect the model to complete all at once. In our work, we found that RLHF models generalise much better to this dataset than SFT models when trained on the AlpacaFarm datasets.