Meta-Llama-3.1-8B-bnb-4bit
Maintainer: unsloth
63
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| 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
The Meta-Llama-3.1-8B-bnb-4bit model is part of the Meta Llama 3.1 collection of multilingual large language models developed by Meta. This 8B parameter model is optimized for multilingual dialogue use cases and outperforms many open source and closed chat models on common industry benchmarks. It uses an auto-regressive transformer architecture and is trained on a mix of publicly available online data. The model supports text input and output in multiple languages including English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.
Similar models in the Llama 3.1 family include the Meta-Llama-3.1-70B and Meta-Llama-3.1-405B which offer larger model sizes for more demanding applications. Other related models include the llama-3-8b from Unsloth which provides a finetuned version of the original Llama 3 8B model.
Model inputs and outputs
Inputs
- Multilingual Text: The model accepts text input in multiple languages including English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.
- Multilingual Code: The model can also accept code snippets in various programming languages.
Outputs
- Multilingual Text: The model generates text output in the same supported languages as the inputs.
- Multilingual Code: The model can generate code outputs in various programming languages.
Capabilities
The Meta-Llama-3.1-8B-bnb-4bit model is particularly well-suited for multilingual dialogue and conversational tasks, outperforming many open source and closed chat models. It can engage in natural discussions, answer questions, and complete a variety of text generation tasks across different languages. The model also demonstrates strong capabilities in areas like reading comprehension, knowledge reasoning, and code generation.
What can I use it for?
This model could be used to power multilingual chatbots, virtual assistants, and other conversational AI applications. It could also be fine-tuned for specialized tasks like language translation, text summarization, or creative writing. Developers could leverage the model's outputs to generate synthetic data or distill knowledge into smaller models. The Llama Impact Grants program from Meta also highlights compelling applications of Llama models for societal benefit.
Things to try
One interesting aspect of this model is its ability to handle code generation in multiple programming languages, in addition to natural language tasks. Developers could experiment with using the model to assist with coding projects, generating test cases, or even drafting technical documentation. The model's multilingual capabilities also open up possibilities for cross-cultural communication and international collaboration.
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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