Package: gpt3datagen
GPT3DataGenGPT3DataGen is a python package that generates fake data for fine-tuning youropenaimodels._      ___      _         _
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( (_) || (_) )| |_ ( )_) |( (_| |( (_| || |_( (_| |( (_) |(  ___/| ( ) |`\__  || ,__/'`\__)`\____)`\__,_)`\__,_)`\__)`\__,_)`\__  |`\____)(_) (_)v1.0.3
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 \___/'(_)                                           \___/'Install with pip. SeeInstall & Usage Guidepipinstall-Ugpt3datagenAlternatively, the following command will pull and install the latest commit
from this repository, along with its Python dependencies:pipinstallgit+https://github.com/donwany/gpt3datagen.git--use-pep517Or git clone repository:gitclonehttps://github.com/donwany/gpt3datagen.gitcdgpt3datagen
makeinstall&&pipinstall-e.To update the package to the latest version of this repository, please run:pipinstall--upgrade--no-deps--force-reinstallgit+https://github.com/donwany/gpt3datagen.gitCommand-Line UsageRun the following to view all available options:gpt3datagen--help
gpt3datagen--versionOutput formats:jsonl,json,csv,tsv,xlsxgpt3datagen\--num_samples500\--max_length2048\--sample_type"classification"\--output_format"jsonl"\--output_dir.

gpt3datagen\--num_samples500\--max_length2048\--sample_typecompletion\--output_formatcsv\--output_dir.

gpt3datagen\--sample_typecompletion\--output_formatjsonl\--output_dir.

gpt3datagen--sample_typecompletion-o.-fjsonl
gpt3datagen--sample_typenews-o.-fjsonlData Format{"prompt":"<prompt text> \n\n###\n\n","completion":" <ideal generated text> END"}{"prompt":"<prompt text> \n\n###\n\n","completion":" <ideal generated text> END"}{"prompt":"<prompt text> \n\n###\n\n","completion":" <ideal generated text> END"}...Basic UsageOnly useful if you clone the repositorypythonprepare.py\--num_samples500\--max_length2048\--sample_type"classification"\--output_format"jsonl"\--output_dir.

pythonprepare.py\--num_samples500\--max_length2048\--sample_type"completion"\--output_format"csv"\--output_dir.

pythonprepare.py\--num_samples500\--max_length2048\--sample_type"completion"\--output_format"json"\--output_dir/Users/<tsiameh>/DesktopValidate Sample Datapipinstall--upgradeopenaiexportOPENAI_API_KEY="<OPENAI_API_KEY>"# validate sample datasets generatedopenaitoolsfine_tunes.prepare_data-f<SAMPLE_DATA>.jsonl
openaitoolsfine_tunes.prepare_data-f<SAMPLE_DATA>.csv
openaitoolsfine_tunes.prepare_data-f<SAMPLE_DATA>.tsv
openaitoolsfine_tunes.prepare_data-f<SAMPLE_DATA>.json
openaitoolsfine_tunes.prepare_data-f<SAMPLE_DATA>.xlsx
openaitoolsfine_tunes.prepare_data-f/Users/<tsiameh>/Desktop/data_prepared.jsonl# fine-tuneopenaiapifine_tunes.create\-t<DATA_PREPARED>.jsonl\-m<BASE_MODEL:davinci,curie,ada,babbage># List all created fine-tunesopenaiapifine_tunes.listTest Runs# For multiclass classificationopenaiapifine_tunes.create\-t<TRAIN_FILE_ID_OR_PATH>\-v<VALIDATION_FILE_OR_PATH>\-m<MODEL>\--compute_classification_metrics\--classification_n_classes<N_CLASSES># For binary classificationopenaiapifine_tunes.create\-t<TRAIN_FILE_ID_OR_PATH>\-v<VALIDATION_FILE_OR_PATH>\-m<MODEL>\--compute_classification_metrics\--classification_n_classes2\--classification_positive_class<POSITIVE_CLASS_FROM_DATASET>ContributePlease seeCONTRIBUTING.LicenseGPT3DataGen is released under the MIT License. See the bundledLICENSEfile
for details.CreditsTheophilus Siameh