LLaMA

Series of large language models...

4.0| Editor Rating

Editor Review

LLaMA is an open-source large language model from Meta, suitable for users requiring local deployment and research. Its multiple parameter versions offer flexibility, but the download and usage process is relatively complex, requiring an application and acceptance of the license agreement. Despite this, it remains an important open-source project, providing rich resources for developers and researchers. However, since some features are spread across multiple repositories, integration and usage may require some time and effort. Recommendation rating: ★★★★☆ (4.0/5.0).

AI Tools Navigator Editorial TeamUpdated: 2026-08-19

What is LLaMA

LLaMA is a series of large language models introduced by Meta, designed to provide researchers and developers with strong natural language processing capabilities. The series includes multiple parameter sizes, ranging B to, suitable for various application scenarios. The code and model weights are hosted on GitHub, but users must apply on the Meta website and accept the license agreement before downloading. With the release of Llama, the relevant GitHub repositories have been consolidated, and additional functional repositories such as llama-models, PurpleLlama, and llama-toolchain have been added to support a more complete Llama Stack. Llama's release has made these models accessible to a broader audience, including individuals, creators, researchers, and businesses. Users can run inference locally, but certain environmental requirements, such as PyTorch and CUDA support, must be met. Additionally, Meta provides download options on Hugging Face, where users must confirm the license agreement and fill out a form to gain access.

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Basic Info

Category:

Company:Meta

Best For

DevelopersResearchers

Difficulty: Intermediate

LLaMA Key Features

Multiple parameter versions
LLaMA offers multiple parameter versions, including,,, and, suitable for different computational resources and task requirements. Users can select the appropriate model version based on their hardware capabilities and application scenarios.
Inference and fine-tuning support
LLaMA supports inference and fine-tuning, allowing users to further train and optimize the models. The official website provides example code to help users get started quickly.
Open-source code and model weights
LLaMA's code and model weights are open-sourced on GitHub, allowing users to freely access and use them. However, users must apply through the Meta website before downloading and accept the relevant use license agreement.
Support for Hugging Face downloads
In addition to GitHub, LLaMA is also available for download on Hugging Face. Users must confirm the license agreement and fill out a form to gain access to the models.

LLaMA Key Advantages

Offers multiple parameter versions suitable for different computational resources and task requirements.
Code and model weights are open-sourced, facilitating research and secondary development.
Supports local inference deployment, suitable for scenarios with data privacy requirements.

LLaMA Use Cases

Natural language processing tasks
LLaMA can be used for various natural language processing tasks, such as text generation, question-answering systems, and language understanding. Its multiple parameter versions are suitable for different computational requirements.
Local inference deployment
Users can deploy LLaMA models for inference in local environments, suitable for scenarios requiring data privacy control and computational resource management. The official website provides example code to assist with deployment.
Research and development
LLaMA provides open-source models and code for researchers and developers, facilitating experimentation, optimization, and expansion. Its model weights and code can serve as a foundation for research and development.

Frequently Asked Questions

How can I download the LLaMA model weights?▼

Users must first visit the Meta website, apply for and accept the license agreement. After approval, Meta will send a signed download link via email. Then users need to run the download.sh script and input the provided link to start the download. Note that the download links expire after 24 hours or after a certain number of downloads. If users encounter a 403 error, they can reapply for a link.

Does LLaMA support downloading on Hugging Face?▼

Yes, LLaMA model weights are also available for download on Hugging Face. Users must confirm the license agreement in the model card of the relevant repository and fill out a form. After submission, access is typically granted within one hour.

Are there any restrictions on using LLaMA?▼

Yes, the use of LLaMA is subject to restrictions outlined in Meta's use policies. Users must carefully read and accept these policies before downloading and using the models. Additionally, ethical and safety considerations may apply, and the official website provides a Responsible Use Guide for reference.