Llama2 13B - Details

Llama2 13B is a large language model developed by Meta Llama, a company, featuring 13 billion parameters. It is available under the Llama 2 Acceptable Use Policy (LLAMA-2-AUP) and Llama 2 Community License Agreement (LLAMA-2-CLA). Llama2 is a collection of large, open-source language models ranging from 7B to 70B parameters.

Llama2 is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters, designed for diverse applications. It includes specialized variations like Llama-2-Chat, optimized for dialogue use cases with enhanced helpfulness and safety. The models leverage an optimized transformer architecture and advanced alignment techniques such as SFT (Supervised Fine-Tuning) and RLHF (Reinforcement Learning with Human Feedback). Trained on 2 trillion tokens of publicly available data, Llama2 emphasizes English language support while maintaining flexibility for other tasks.

Llama2 13B is a mid-scale large language model with 13 billion parameters, placing it in the range of models optimized for balanced performance and moderate complexity. Its 4k context length supports short to moderate tasks but limits its ability to handle very long texts. The parameter size allows for efficient resource use while maintaining versatility, while the context length ensures effective handling of typical conversational and textual tasks. These specifications make it suitable for applications requiring a trade-off between capability and computational efficiency.

• Name: Llama2 13B
• Parameter Size: 13b
• Context Length: 4k
• Implications: Mid-scale performance, efficient resource use, limited for very long texts.

Llama2 13B is a versatile large language model with 13 billion parameters that offers possible applications across various domains. Its design allows for possible use in commercial settings, where it could support tasks like content creation or customer interaction. It also presents possible value for research purposes, enabling exploration of language patterns or model behavior. As an assistant-like chat tool, it could facilitate conversational interactions, though its effectiveness would depend on specific configurations. Additionally, it could be used for natural language generation tasks, such as drafting text or generating creative content, but these possible uses require careful evaluation. The model’s capabilities are broad, but any possible application should be thoroughly tested to ensure alignment with specific goals.

• commercial use
• research use
• assistant-like chat
• natural language generation tasks

Llama2 13B is a large language model with 13 billion parameters that offers possible applications in areas such as commercial use, where it could support tasks like content creation or customer interaction. It also presents possible value for research use, enabling exploration of language patterns or model behavior. As an assistant-like chat tool, it could facilitate conversational interactions, though its effectiveness would depend on specific configurations. Additionally, it could be used for natural language generation tasks, such as drafting text or generating creative content, but these possible uses require careful evaluation. The model’s capabilities are broad, but any possible application should be thoroughly tested to ensure alignment with specific goals.

• commercial use
• research use
• assistant-like chat
• natural language generation tasks

Llama2 13B's medium q4 version is optimized for a balance between precision and performance, requiring a GPU with at least 16GB VRAM for efficient operation. This quantized version reduces memory usage compared to higher-precision formats like fp16, making it suitable for systems with moderate hardware capabilities. However, the exact requirements may vary based on the specific implementation and workload.

• fp16, q2, q3, q4, q5, q6, q8

Llama2 13B is a mid-scale large language model developed by Meta Llama, featuring 13 billion parameters as part of the Llama2 series, which ranges from 7B to 70B parameters. It is designed for balanced performance and resource efficiency, making it suitable for a variety of applications while maintaining open-source accessibility.

Huggingface Model Page
Ollama Model Page