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Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.

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01MCES10-Software /Python-Code-Solutions Python Code Solutions Features 1000k of Python Code Solutions for Text Generation and Question Answering Python Coding Problems labelled by topic and difficulty Recommendations Train your Model on Logical Operations and Mathematical Problems Before Training it on this. This is optional for Fine Tuning 2B parameter + models. Format the prompts in a orderly way when formatting data eg. {question} Solution: {solution} Topic: {topic} textquestion-answering10K<n<100K0 likes621 downloads1y agoHugging Face02MCES10-Software /CPP-Code-Solutions C++ Code Solutions Features 1000k of Python Code Solutions for Text Generation and Question Answering C++ Coding Problems labelled by topic and difficulty Recommendations Train your Model on Logical Operations and Mathematical Problems Before Training it on this. This is optional for Fine Tuning 2B parameter + models. Format the prompts in a orderly way when formatting data eg. {question} Solution: {solution} Topic: {topic} textquestion-answering10K<n<100K0 likes31 downloads1y agoHugging Face03MCES10-Software /JS-Code-Solutions Python Code Solutions Features 1000k of JS Code Solutions for Text Generation and Question Answering JS Coding Problems labelled by topic and difficulty Recommendations Train your Model on Logical Operations and Mathematical Problems Before Training it on this. This is optional for Fine Tuning 2B parameter + models. Format the prompts in a orderly way when formatting data eg. {question} Solution: {solution} Topic: {topic} textquestion-answering10K<n<100K1 likes22 downloads1y agoHugging Face04SoftAge-AI /sft-conversational_datasetgatedQuestion – Answer DatasetThe dataset contains 400 queries from two domains: Current Affairs and Creative Writing. It serves as a versatile resource for Natural Language Processing (NLP) tasks, including text classification, information retrieval, and model training. Data attributes: Query: The user-generated question. Data type: string. Answer: The response provided by a team of writers and editors in markdown format, containing information related to the query. Citations: Up to 4 credible… See the full description on the dataset page: https://huggingface.co/datasets/SoftAge-AI/sft-conversational_dataset.textquestion-answeringn<1K5 likes11 downloads3y agoHugging Face

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