Llama-3.2-3B-Instruct
Maintainer: meta-llama
235
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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 Llama-3.2-3B-Instruct model is part of the Meta Llama 3.2 collection of multilingual large language models (LLMs). It is a pretrained and instruction-tuned generative model optimized for multilingual dialogue use cases, including agentic retrieval and summarization tasks. The Llama 3.2 models outperform many available open-source and closed chat models on common industry benchmarks. This 3B parameter model is one of the smaller variants in the Llama 3.2 family, which also includes larger 1B and 8B versions.
The Llama 3.2 models use an optimized transformer architecture and were trained using a combination of supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align the models with human preferences for helpfulness and safety. Meta developed the Llama 3.2 models and they are available under the Llama 3.2 Community License.
Model inputs and outputs
Inputs
- Multilingual Text: The
Llama-3.2-3B-Instructmodel accepts multilingual text as input, with official support for 8 languages: English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai. - Multilingual Code: In addition to natural language text, the model can also handle code inputs across these supported languages.
Outputs
- Multilingual Text: The model generates multilingual text responses in the supported languages.
- Multilingual Code: The model can also generate code outputs in the supported languages.
Capabilities
The Llama-3.2-3B-Instruct model is capable of engaging in multilingual dialogue, answering questions, summarizing information, and performing a variety of other natural language processing tasks. Its instruction-tuning allows it to follow prompts and execute commands in a helpful and reliable manner. The model has also demonstrated strong performance on benchmarks testing reasoning, commonsense understanding, and other cognitive capabilities.
What can I use it for?
The Llama-3.2-3B-Instruct model is intended for commercial and research use in multiple languages. Its instruction-tuned text-only capabilities make it well-suited for building multilingual assistant applications, chatbots, and other dialogue-based systems. Developers can also fine-tune the model for a variety of other natural language generation tasks, such as text summarization, language translation, and content creation.
Things to try
One interesting aspect of the Llama-3.2-3B-Instruct model is its ability to handle code inputs and outputs. Developers could experiment with using the model to generate, explain, or modify code snippets in the supported languages. Another intriguing possibility is leveraging the model's multilingual capabilities to build cross-lingual applications, where users can seamlessly interact in their preferred language.
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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