
# dolly_hhrlhf-text2text

This is `mosaicml/dolly_hhrlhf` with the following changes:

- clean up/adapt `prompt` column for the `text2text-generation` task (no need for a special template)
- split the original `train` set into a 95% train and an explicit validation set (5%)
- fixed extra spaces in puncuation (as this is not a French dataset)

details on extra spaces:

```
Original sentence 1: How can I be healthy ?
Fixed sentence 1: How can I be healthy?
```
task_categories:text2text-generation size_categories:10K<n<100K source_datasets:mosaicml/dolly_hhrlhf language:en license:cc-by-sa-3.0 instruct region:us
{"language": ["en"], "license": "cc-by-sa-3.0", "size_categories": ["10K<n<100K"], "source_datasets": "mosaicml/dolly_hhrlhf", "task_categories": ["text2text-generation"], "tags": ["instruct"]}
TAGS
#task_categories-text2text-generation #size_categories-10K<n<100K #source_datasets-mosaicml/dolly_hhrlhf #language-English #license-cc-by-sa-3.0 #instruct #region-us 


# dolly_hhrlhf-text2text

This is 'mosaicml/dolly_hhrlhf' with the following changes:

- clean up/adapt 'prompt' column for the 'text2text-generation' task (no need for a special template)
- split the original 'train' set into a 95% train and an explicit validation set (5%)
- fixed extra spaces in puncuation (as this is not a French dataset)

details on extra spaces:


# dolly_hhrlhf-text2text

This is 'mosaicml/dolly_hhrlhf' with the following changes:

- clean up/adapt 'prompt' column for the 'text2text-generation' task (no need for a special template)
- split the original 'train' set into a 95% train and an explicit validation set (5%)
- fixed extra spaces in puncuation (as this is not a French dataset)

details on extra spaces:
TAGS
#task_categories-text2text-generation #size_categories-10K<n<100K #source_datasets-mosaicml/dolly_hhrlhf #language-English #license-cc-by-sa-3.0 #instruct #region-us 
 # dolly_hhrlhf-text2text

This is 'mosaicml/dolly_hhrlhf' with the following changes:

- clean up/adapt 'prompt' column for the 'text2text-generation' task (no need for a special template)
- split the original 'train' set into a 95% train and an explicit validation set (5%)
- fixed extra spaces in puncuation (as this is not a French dataset)

details on extra spaces: