JCX-kcuf/Llama-2-7b-hf-gpt-3.5-80k
TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:4kPublished:Mar 10, 2024License:apache-2.0Architecture:Transformer Open Weights Cold

JCX-kcuf/Llama-2-7b-hf-gpt-3.5-80k is a 7 billion parameter language model based on Meta's Llama-2 architecture, fine-tuned using distillation data from GPT-3.5. This model is designed to emulate the conversational style and safety guidelines of GPT-3.5, making it suitable for helpful, respectful, and honest assistant applications. It processes queries in a Llama-2-compatible instruction format, ensuring safe and socially unbiased responses. Its primary strength lies in generating coherent and ethically sound text based on its GPT-3.5 distilled training.

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What is JCX-kcuf/Llama-2-7b-hf-gpt-3.5-80k?

This model is a 7 billion parameter large language model built upon the Meta Llama-2-7b-hf base architecture. Its key differentiator is the fine-tuning process, which utilized distillation data from GPT-3.5. This approach aims to imbue the model with the conversational characteristics and safety protocols observed in GPT-3.5.

Key Capabilities

  • GPT-3.5-like Response Generation: Through distillation, the model is trained to produce outputs that align with the helpful, respectful, and honest nature of GPT-3.5.
  • Safety and Bias Mitigation: It is designed to avoid harmful, unethical, racist, sexist, toxic, dangerous, or illegal content, promoting socially unbiased and positive responses.
  • Llama-2 Query Format: The model adheres to the standard Llama-2 instruction format, including system prompts for guiding its behavior.

Good For

  • Assistant Applications: Ideal for developing conversational agents that require a helpful and safe demeanor.
  • Content Generation with Safety Constraints: Suitable for tasks where ethical and unbiased output is paramount.
  • Research into Model Distillation: Provides a practical example of transferring knowledge from a larger, proprietary model (GPT-3.5) to a smaller, open-source base (Llama-2).