Llama-3-8B-Instruct-64k-GGUF
| Property | Value |
|---|---|
| Parameter Count | 8.03B |
| Model Type | Instruction-tuned Language Model |
| Format | GGUF (Various bit precisions) |
| Context Length | 64,000 tokens |
| Author | MaziyarPanahi |
What is Llama-3-8B-Instruct-64k-GGUF?
This model is a quantized version of the LLaMA-3 architecture, specifically optimized for efficient local deployment using the GGUF format. It features an impressive 64k context window and supports multiple quantization levels (2-bit to 8-bit precision) to balance performance and resource requirements.
Implementation Details
The model leverages the GGUF format, which replaced the older GGML format in August 2023. It's designed for optimal performance in local environments and supports various client applications and libraries.
- Multiple quantization options (2-bit to 8-bit precision)
- 64k token context window
- Instruction-tuned architecture
- Optimized for local deployment
Core Capabilities
- Text generation and completion
- Conversational AI applications
- Compatible with multiple deployment platforms
- Supports GPU acceleration on compatible platforms
Frequently Asked Questions
Q: What makes this model unique?
The model combines the power of LLaMA-3 architecture with extensive context length (64k) and flexible quantization options, making it highly adaptable for various deployment scenarios while maintaining performance.
Q: What are the recommended use cases?
The model is particularly well-suited for local deployment in applications requiring text generation, conversational AI, and tasks benefiting from long context windows. It can be implemented using various platforms like LM Studio, text-generation-webui, or KoboldCpp.
