Llama 3.1 Tulu 3 8B Preference Mixture
Structured dataset for supervised learning training of LLM models, containing annotations of human preferences on generated outputs.
Description
Llama 3.1 Tulu 3 8B Preference Mixture is a structured dataset containing more than 270,000 examples of preference annotations, used to refine Llama 3.1 Tulu 3 8B language models using supervised learning methods based on human feedback.
What is this dataset for?
- Train LLM models to better understand user preferences
- Refine the outputs generated by models through supervised learning
- Contribute to the development of more aligned and efficient models
Can it be enriched or improved?
Yes, this dataset can be enriched by additional annotations or more diverse user feedback, in order to improve the quality of preferences and the coverage of use cases.
🔎 In summary
🧠 Recommended for
- NLP researchers
- RLHF teams
- Aligned model developers
🔧 Compatible tools
- Hugging Face Transformers
- DeepSpeed
- LoRa
- PEFT
💡 Tip
Use this dataset in conjunction with human annotations specific to your domain to maximize relevance.
Frequently Asked Questions
Can this dataset be used to train models other than Llama 3.1?
Yes, although designed for Llama 3.1, preference data can be adapted to other similar LLM architectures.
Does the dataset contain annotator metadata?
The description is not specific, but generally this type of dataset focuses on preferences, not on annotatory information.
Can we combine this dataset with other data preferably?
Yes, it is even recommended to improve the diversity and quality of preferences used during training.
