jondurbin/airoboros-7b-gpt4-1.4.1-qlora
The jondurbin/airoboros-7b-gpt4-1.4.1-qlora is a 7 billion parameter LLaMA-based model fine-tuned using QLoRA with a 4096-token context length. Developed by jondurbin, this model utilizes entirely synthetic training data generated by GPT-4, focusing on enhanced multi-turn conversations, coding examples across 10 languages, and improved roleplay. It excels in context-obedient question answering and diverse creative tasks, including coding, writing, and word games.
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Model Overview
This model, airoboros-7b-gpt4-1.4.1-qlora, is a 7 billion parameter LLaMA-based model developed by jondurbin. It is a QLoRA fine-tune, distinguishing it from full fine-tune versions, and was trained on a completely synthetic dataset generated by GPT-4 (version 1.4.1).
Key Capabilities & Enhancements
- Synthetic Data Training: Utilizes a unique dataset (jondurbin/airoboros-gpt4-1.4.1) for fine-tuning, created entirely by GPT-4.
- Improved Conversations: Features fixed and expanded examples of multi-character, multi-turn conversations.
- Enhanced Coding: Includes coding examples in 10 languages sourced from the rosettacode.org dataset, with a "PLAINFORMAT" option for code-only output.
- Context-Obedient QA: Specifically tuned to ignore prior knowledge and answer questions strictly based on provided context, reducing hallucinations. It uses a verbose, delimited format for closed-context instructions.
- Diverse Applications: Demonstrates proficiency in roleplay, jokes, riddles, word games, multiple-choice questions, and creative writing.
Usage & Licensing
This model is intended and licensed for research use only (cc-nc-4.0), due to its LLaMA base and the use of OpenAI-generated data, which restricts commercial application. It is designed to be run with a fork of FastChat, supporting multi-line prompts and optional history management.