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Llama3-TenyxChat-70B

Maintainer: tenyx

Total Score

53

Last updated 5/16/2024

📶

PropertyValue
Model LinkView on HuggingFace
API SpecView on HuggingFace
Github LinkNo Github link provided
Paper LinkNo paper link provided

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Model overview

Llama3-TenyxChat-70B is a fine-tuned 70B Instruct model developed by Tenyx Research using the Direct Preference Optimization (DPO) framework. The model is based on the open-source Llama3-70B and has been further fine-tuned to function as a useful language model assistant through preference tuning. Tenyx used their proprietary fine-tuning approach which shows an increase in MT-Bench performance without a drop in the model's performance on other benchmarks.

Model inputs and outputs

Inputs

  • The model takes text input only.

Outputs

  • The model generates text and code outputs.

Capabilities

Llama3-TenyxChat-70B has been optimized for dialogue use cases and outperforms many available open-source chat models on common industry benchmarks. The model was trained using the UltraFeedback dataset, which aims to align the model's preferences with human preferences for helpfulness and safety.

What can I use it for?

Llama3-TenyxChat-70B can be used for a variety of natural language generation tasks, such as chatbots, personal assistants, and language-based applications. The model's fine-tuning on the UltraFeedback dataset makes it well-suited for conversational AI use cases where helpfulness and safety are important.

Things to try

You can try using Llama3-TenyxChat-70B to build a personalized chatbot or virtual assistant tailored to your specific needs. The model's strong performance on benchmarks like MT-Bench suggests it could be a powerful tool for generating high-quality, helpful text responses. Additionally, the model's safety-focused fine-tuning may make it a good choice for applications where you need to ensure appropriate and responsible language outputs.



This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!

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