Smaug-Llama-3-70B-Instruct
Maintainer: abacusai
140
⚙️
| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
Smaug-Llama-3-70B-Instruct is a large language model developed by Abacus.AI using a new Smaug recipe for improving performance on real-world multi-turn conversations. This model was built by fine-tuning the meta-llama/Meta-Llama-3-70B-Instruct model. The Smaug-Llama-3-70B-Instruct model outperforms the Llama-3-70B-Instruct substantially and is on par with GPT-4-Turbo on the MT-Bench benchmark.
Similar models include the Llama-3-Smaug-8B model, which used the Smaug recipe on the smaller 8B version of the Meta Llama 3 model. The Meta-Llama-3-70B-Instruct and Meta-Llama-3-8B-Instruct models are the original instruction-tuned versions released by Meta.
Model inputs and outputs
Inputs
- The model takes in text inputs only.
Outputs
- The model generates text and code outputs.
Capabilities
The Smaug-Llama-3-70B-Instruct model excels at a variety of tasks, including multi-turn conversations, general knowledge, and coding. It has shown strong performance on benchmarks like MT-Bench and is on par with GPT-4-Turbo.
What can I use it for?
The Smaug-Llama-3-70B-Instruct model can be used for a wide range of applications that require natural language understanding and generation, such as chatbots, virtual assistants, content creation, and code generation. Its strong performance on multi-turn conversations makes it well-suited for building engaging and helpful conversational AI systems.
Things to try
Developers can experiment with using the Smaug-Llama-3-70B-Instruct model for tasks like language translation, text summarization, and creative writing. The model's ability to engage in multi-turn dialogues could also be leveraged to build advanced conversational AI applications.
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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