Llama-4-Maverick-17B-128E-Instruct-FP8-Original
| Property | Value |
|---|---|
| Model Size | 17B parameters |
| Developer | Meta |
| Quantization | FP8 |
| Model URL | HuggingFace/meta-llama |
What is Llama-4-Maverick-17B-128E-Instruct-FP8-Original?
Llama-4-Maverick is Meta's advanced instruction-tuned language model, featuring 17 billion parameters and optimized using FP8 quantization. This model represents a significant evolution in Meta's Llama series, designed specifically for instruction-following and task completion.
Implementation Details
The model employs FP8 quantization, a technique that reduces the model's memory footprint while maintaining performance. With 128 expert layers (indicated by 128E in the name), it utilizes a mixture of experts architecture for enhanced efficiency.
- 17B parameter architecture optimized for instruction following
- FP8 quantization for efficient deployment
- 128 expert layers for improved performance
- Original instruction-tuned version
Core Capabilities
- Advanced instruction following and task completion
- Efficient processing through FP8 quantization
- Improved performance through mixture of experts
- Compliance with Meta's privacy standards
Frequently Asked Questions
Q: What makes this model unique?
The combination of FP8 quantization with a 17B parameter architecture and 128 expert layers makes this model particularly efficient while maintaining high performance on instruction-following tasks.
Q: What are the recommended use cases?
This model is particularly suited for instruction-following applications, natural language processing tasks, and scenarios where efficient deployment of large language models is crucial.
