Llama Howto
LLaMA (Large Language Model Meta AI) is Meta's open-source family of large language models offering scalable, multilingual, and multimodal capabilities that can be fine-tuned, distilled and deployed anywhere.
View MoreHow to Use Llama
Choose a Llama Access Method: Select from multiple options: Hugging Face, GPT4ALL, Ollama, or direct download from Meta AI's official website
Set Up Environment: Install necessary tools based on chosen method. For example, if using GPT4ALL, download and install the application from the official download page
Select Llama Model: Choose from available models: Llama 3.1 (8B, 405B), Llama 3.2 (1B, 3B, 11B, 90B), or Llama 3.3 (70B) based on your needs and computational resources
Download Model: Download the selected model. For GPT4ALL, use the Downloads menu and select Llama model. For Hugging Face, access through their platform interface
Configure Settings: Set up parameters like maximum tokens, temperature, and other model-specific settings depending on your use case
Integration: Integrate the model into your application using provided APIs or SDKs. Choose from Python, Node, Kotlin, or Swift programming languages
Test Implementation: Start with basic prompts to test the model's functionality and adjust settings as needed for optimal performance
Deploy: Deploy your implementation either locally, on-premises, cloud-hosted, or on-device at the edge depending on your requirements
Llama FAQs
Llama is a family of open-source AI models developed by Meta that can be fine-tuned, distilled and deployed anywhere. It includes multilingual text-only models, text-image models, and various sizes of models optimized for different use cases.
Llama Monthly Traffic Trends
Llama achieved 1.7M visits with a 69.5% growth in July. The release of Llama 4 with a mixture of experts architecture and multimodal capabilities likely attracted more users, while the LlamaCon AI conference and new API further boosted interest and adoption.
View history traffic
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