Llama-4-Maverick-17B-128E-Instruct-FP8
| Property | Value |
|---|---|
| Author | Meta |
| Parameter Count | 17 Billion |
| Model Type | Instruction-tuned Language Model |
| Quantization | FP8 |
| Model URL | https://huggingface.co/meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8 |
What is Llama-4-Maverick-17B-128E-Instruct-FP8?
Llama-4-Maverick-17B-128E-Instruct-FP8 is Meta's advanced language model, representing a significant evolution in the Llama series. This variant features 17 billion parameters and is specifically optimized for instruction-following tasks, implementing FP8 quantization for improved efficiency while maintaining performance.
Implementation Details
The model incorporates several technical innovations, including 128-token context enhancement (indicated by 128E in the name) and FP8 quantization for reduced memory footprint and faster inference. It's built on Meta's proven Llama architecture while introducing specific optimizations for instruction-based tasks.
- FP8 quantization for efficient deployment
- 128-token context enhancement for improved understanding
- 17B parameter architecture balancing performance and resource usage
- Instruction-tuned specifically for following complex prompts
Core Capabilities
- Enhanced instruction following and task completion
- Efficient processing with FP8 quantization
- Improved context handling with 128-token enhancement
- Balanced performance for enterprise applications
Frequently Asked Questions
Q: What makes this model unique?
This model combines Meta's proven Llama architecture with FP8 quantization and specific optimizations for instruction-following tasks, making it particularly efficient for deployment while maintaining high performance.
Q: What are the recommended use cases?
The model is particularly well-suited for instruction-based applications, enterprise deployments requiring efficient resource usage, and scenarios where balanced performance and memory footprint are crucial.
