Datasets:

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OpenAssistant

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oasst1

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OpenAssistant 1.08k

Reveals the conversational structure by pairing user prompts with their immediate assistant responses, exposing dialogue patterns and potential conversation flows in the training data.

Reveals the interaction between prompts and completions in Indonesian language, providing insight into the dialogue flow and content.

Provides a random sample of prompt-completion pairs in English, which can be useful for evaluating the quality and coherence of assistant responses in a conversational dataset.

Retrieves pairs of prompts and their corresponding completions in English, providing insight into the interaction patterns between users and assistants.

Retrieves unique prompt-completion pairs from the dataset, providing a clear view of the interactions between prompts and their corresponding assistant responses.

Provides a meaningful sample of user queries and corresponding assistant responses in English, helping to understand the nature of interactions and the quality of responses in the dataset.

This query pairs user queries with corresponding assistant responses, filtering out very short messages, which can help understand the dynamics of user-assistant interactions.

Provides a paired list of user queries and corresponding assistant responses, useful for understanding the interaction patterns in a conversational dataset.

Reveals example dialogues by pairing user queries with corresponding assistant responses, providing insight into how the assistant interacts with users.

Reveals multi-turn conversation patterns, showing how user queries and assistant responses evolve over multiple exchanges, providing useful insights into dialogue dynamics.

Reveals a sequence of interactions between an assistant and a user, along with the assistant's final response, helping to understand the flow and context of the conversation.

Retrieves all English top-level posts (those without parent comments) which provides basic filtering but offers limited analytical value beyond identifying standalone content.

Filters for Spanish-language posts without parents, revealing standalone posts in Spanish that could be used to understand conversational context in Spanish social media data.

Retrieves English and Spanish texts that are root-level posts (no parent_id), which helps identify main discussion threads but doesn't provide deeper analytical insights.

Retrieves 10 Hungarian language training examples, providing basic dataset sampling but offering no analytical insights or patterns.

Retrieves top-level posts from a threaded discussion dataset that have no parent replies, providing basic structure information but offering limited analytical insights.

Filters for top-level English posts in a dataset, showing basic language distribution but providing minimal analytical insights beyond simple data retrieval.

Retrieves the first 10 English root-level posts from the training dataset, providing basic filtering but offering limited analytical insight beyond confirming data structure.

Retrieves English text entries shorter than 100 characters that are parent posts, providing basic filtering of the dataset.

Retrieves records from the train dataset where the parent_id is NULL, providing a basic filter but limited analytical value.

Retrieves English prompts from the dataset that do not have a parent, providing a basic view of initial prompts in English.

Lists all unique languages present in the dataset, providing basic information about language diversity.

Retrieves all English entries without a parent ID, providing a basic filtered view of the dataset.

Retrieves all English entries without a parent, providing a basic filtered view of the dataset.

Retrieves all records from the 'train' dataset where the language is Arabic, providing a basic filter of the data.