abacusai/Liberated-Qwen1.5-72B

TEXT GENERATIONConcurrency Cost:4Model Size:72.3BQuant:FP8Ctx Length:32kPublished:Feb 29, 2024License:tongyi-qianwenArchitecture:Transformer0.1K Cold

Liberated-Qwen1.5-72B is a 72.3 billion parameter language model developed by AbacusAI and Eric Hartford, fine-tuned from Qwen/Qwen1.5-72B with a 32768 token context length. It is specifically designed to enhance compliance with system prompts and handle long, multi-turn conversations, addressing a common limitation in open-source models. This model is trained on open-source datasets, including the novel SystemChat dataset, and is released without guardrails or censorship, requiring users to implement their own alignment layers.

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Liberated-Qwen1.5-72B Overview

Liberated-Qwen1.5-72B is a 72.3 billion parameter language model developed by AbacusAI and Eric Hartford, built upon the Qwen/Qwen1.5-72B base. This model is uniquely fine-tuned to improve system prompt compliance and performance in long, multi-turn conversations, a critical area where many open-source models often fall short. It leverages a 32,768 token context length from its base model, with fine-tuning performed using 8k sequence length inputs.

Key Capabilities

  • Enhanced System Prompt Adherence: Specifically trained to follow system instructions more consistently, even with complex or mechanical prompts.
  • Improved Multi-turn Conversation: Excels in maintaining context and coherence over extended dialogues.
  • Uncensored Output: The model is released without inherent guardrails or censorship, offering raw generative capabilities. Users are advised to implement their own alignment layers for responsible deployment.
  • Strong Base Performance: Preserves a good MMLU score of 77.13, indicating robust general knowledge and reasoning.

Good For

  • Applications requiring strict adherence to predefined system instructions.
  • Building chatbots or conversational agents that need to manage long, complex interactions.
  • Use cases where an uncensored model is preferred for research or specific content generation, with user-implemented safety layers.
  • Developers looking for a powerful 72B parameter model with a focus on conversational compliance and flexibility.