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YAML Metadata Warning:The task_categories "reasoning" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
Obekt Micro Reasoning Dataset (v0.1)
Dataset Description
This is a "micro" dataset containing questions, answers, and reasoning traces. It is generated using the Xiaomi MiMo V2 Flash LLM and is intended for experimental purposes, quick prototyping, and fine-tuning trials where reasoning capability is a focus.
Source Model: xiaomi/mimo-v2-flash
Contains
- obekt-question-answer-reasoning-micro-v0.1.csv: The main data file.
- Columns:
question: The input query.answer: The direct answer.reasoning: The chain-of-thought or explanation leading to the answer.
Disclaimer: Unverified Synthetic Data
This data is 100% synthetic and produced by an AI model.
- Unverified Accuracy: The content is generated and has not been verified by human experts.
- Experimental Use Only: Use this for testing pipelines, fine-tuning mechanics, or analyzing model outputs. Do not rely on it for factual accuracy in critical domains.
Usage
Streaming
Because this dataset is uploaded via push_to_hub, it is stored in Parquet format, enabling efficient streaming.
from datasets import load_dataset
# Load the dataset in streaming mode
dataset = load_dataset("obekt/obekt-question-answer-reasoning-micro-v0.1", streaming=True)
# Iterate through the first few examples
for i, example in enumerate(dataset["train"]):
print("Q:", example['question'])
print("Reasoning:", example['reasoning'])
print("A:", example['answer'])
if i == 2: break
License
MIT License
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