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OLMo 2 1124 13B Preference Mixture

Large-scale multilingual preference mixture dataset

CommonProductOthersDatasetMultilingual

The OLMo 2 1124 13B Preference Mixture is a large multilingual dataset provided by Hugging Face, containing 377.7k generated pairs, aimed at training and optimizing language models, particularly in preference learning and instruction following. Its significance lies in providing a diverse and large-scale data environment that aids in the development of more accurate and personalized language processing technologies.

OLMo 2 1124 13B Preference Mixture

Includes synthetic data from multiple sources for generating preference and instruction-following data.
Supports various languages and dialects
enhancing the multilingual capabilities of models.
Provides a substantial amount of text pairs for fine-tuning and optimizing large language models.
The dataset has been cleaned to remove ShareGPT and TruthfulQA instances
improving data quality.
Supports research and educational use
adhering to Ai2's responsible usage guidelines.
Includes outputs from various models such as Mistral
Tulu

The target audience includes researchers
developers
and educational institutions in the field of natural language processing. They can utilize this dataset to train and enhance language models
particularly in contexts that require understanding and generating text that aligns with specific user preferences.

Researchers use the dataset to train a model capable of understanding and generating user-preferred text.
Developers leverage the dataset to fine-tune a chatbot
enabling it to provide personalized responses based on user preferences.
Educational institutions use the dataset as a teaching resource to help students understand preference recognition and handling in natural language processing.

1. Visit the Hugging Face website and search for the 'OLMo 2 1124 13B Preference Mixture' dataset.
2. Read the dataset description and usage guidelines to understand its structure and features.
3. Download the dataset files
choosing the appropriate format as needed (e.g.
Parquet).

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