hSSKJrJr SSKJr SSKJr SSKJr SSK J r \"SS55r Sr \"S 5r \S :Xa\ "\ 5r\R!5Sr\"S S S 9r\R'SS\R(S9r\R+\ /SQ\R,\R.S.\R(S9r\R1SSS9r\R2(a6\R3\R45 \ R3\R4SS9 ggg)) dataclassfield)Optional) load_dataset) ModelCard)HfArgumentParserc\rSrSr%Sr\"SS/SQS.S9r\\S'\"S S /S QS.S9r \\S '\"S SS0S9r \ \S'\"SSS0S9r \\S'\"SSS0S9r \\\S'Srg)ScriptArgumentsa Arguments for the script. Args: model_name (`str`, *optional*, defaults to `"gpt-3.5-turbo"`): Language model to target. Possible values are: aspect (`str`, *optional*, defaults to `"helpfulness"`): Aspect to target. push_to_hub (`bool`, *optional*, defaults to `False`): Whether to push the dataset to the Hugging Face Hub. repo_id (`str`, *optional*, defaults to `"trl-lib/ultrafeedback-gpt-3.5-turbo-helpfulness"`): Hugging Face repository ID to push the dataset to. dataset_num_proc (`int` or `None`, *optional*, defaults to `None`): Number of workers to use for dataset processing. gpt-3.5-turbozLanguage model to target.)z alpaca-7bbardzfalcon-40b-instructr zgpt-4zllama-2-13b-chatzllama-2-70b-chatzllama-2-7b-chatz mpt-30b-chatz pythia-12bstarchatz ultralm-13bz ultralm-65bz vicuna-33bz wizardlm-13bz wizardlm-70bz wizardlm-7b)helpchoices)defaultmetadata model_name helpfulnesszsAspect to target. Possible values are: 'helpfulness' (default), 'honesty', 'instruction-following', 'truthfulness'.)rhonestyzinstruction-following truthfulnessaspectFrz4Whether to push the dataset to the Hugging Face Hub. push_to_hubz/trl-lib/ultrafeedback-gpt-3.5-turbo-helpfulnessz2Hugging Face repository ID to push the dataset to.repo_idNz0Number of workers to use for dataset processing.dataset_num_proc)__name__ __module__ __qualname____firstlineno____doc__rrstr__annotations__rrboolrrrint__static_attributes__rY/home/james-whalen/.local/lib/python3.13/site-packages/examples/datasets/ultrafeedback.pyr r s / J27Z FCPQKANOGS',LM'hsmr&r cSUSS./nUSRU5nUSUSnSUS./n[USUSUS 5nUS :nX6US .$) Nuser instruction)rolecontentmodels completionsresponse assistant annotationsRating)prompt completionlabel)indexr$) examplerrr4 model_indexresponse_contentr5scorer6s r'to_unpaired_preferencer<Xs'-*@A BF(#))*5K}-k::F&3CDEJ  &{3MB6J8T UE QJE GGr&a --- tags: [trl] --- # UltraFeedback GPT-3.5-Turbo Helpfulness Dataset ## Summary The UltraFeedback GPT-3.5-Turbo Helpfulness dataset contains processed user-assistant interactions filtered for helpfulness, derived from the [openbmb/UltraFeedback](https://huggingface.co/datasets/openbmb/UltraFeedback) dataset. It is designed for fine-tuning and evaluating models in alignment tasks. ## Data Structure - **Format**: [Conversational](https://huggingface.co/docs/trl/main/dataset_formats#conversational) - **Type**: [Unpaired preference](https://huggingface.co/docs/trl/main/dataset_formats#unpaired-preference) Column: - `"prompt"`: The input question or instruction provided to the model. - `"completion"`: The model's response to the prompt. - `"label"`: A binary value indicating whether the response is sufficiently helpful. ## Generation script The script used to generate this dataset can be found [here](https://github.com/huggingface/trl/blob/main/examples/datasets/ultrafeedback.py). __main__zopenbmb/UltraFeedbacktrain)splitc.[RUS;$)Nr-) script_argsr)r8s r'rBs ..'(2CCr&F)batchednum_proc)sourcer*r-r.correct_answersincorrect_answers)rr)remove_columns fn_kwargsrDg?*) test_sizeseeddataset) repo_typeN) dataclassesrrtypingrdatasetsrhuggingface_hubr transformersrr r< model_cardrparserparse_args_into_dataclassesrArMfilterrmaprrtrain_test_splitrrrr&r'rZs,)!%) == =@H 4 z o .F446q9K2'BGnnC--G kkq!,!7!7;CUCUV-- G &&B&?GK//0{22iH'r&