Synthia-v1.3

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Synthia-v1.3

Synthetic training data for LLM development

By Migel Tissera (From Huggingface) [source]

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About this dataset

The train.csv dataset, available on Kaggle, is a specially curated synthetic training dataset created for researchers working on the development and enhancement of the migtissera/Synthia-v1.3 system. Designed to provide valuable data for the improvement of this system, the dataset comprises three informative columns: system, instruction, and response.

With meticulous attention given to detail and accuracy, each entry in this dataset carries significant value in furthering the understanding and optimization of the migtissera/Synthia-v1.3 system. The system column denotes the name or identifier of the specific system responsible for generating each response in the dataset.

Moreover,the instruction column represents text-based instructions that were inputted into the migtissera/Synthia-v1.3 system to prompt its response generation process. These instructions may vary in length, context, complexity, and language but collectively form a diverse range of stimuli presented to evaluate and analyze how well-equipped this automated system is at generating appropriate responses.

The response column reflects outputs generated by running these corresponding instructions through the migtissera/Synthia-v1.3 system. Researchers can extensively study these responses to assess linguistic fluency, coherence with respect to input instructions,vocabulary usage relevance,domain-specific knowledge incorporation,and any other relevant performance metrics tied directly or indirectly to natural language processing capabilities.

This carefully constructed synthetic training dataset acts as an indispensable resource for researchers determined to explore innovative strategies aimed at refining machine learning models and boosting human-machine interaction quality levels within automated response generation systems like migtissera/Synthia-v1.3. With valuable insights awaiting those who delve into it,the potential advancements scope in natural language processing achievable with this rich training data is vast

How to use the dataset

• Understanding the dataset:
  • The dataset consists of three columns: system, instruction, and response.
  • The system column represents the name or identifier of the system that generated each response.
  • The instruction column contains the instruction given to the system.
  • The response column corresponds to the generated response from the system based on the given instruction.
• Exploring data patterns:
  • Start by exploring different instructions and their corresponding responses in order to get familiar with various types of interactions between users and systems.
  • Analyze patterns in instructions that prompt specific responses, considering both syntactical and semantic aspects.

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: train.csv

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit Migel Tissera (From Huggingface).