Meta-Llama-3.1-8B-Instruct-GGUF
| Property | Value |
|---|---|
| Parameter Count | 8.03B |
| License | LLaMA 3.1 |
| Supported Languages | English, German, French, Italian, Portuguese, Hindi, Spanish, Thai |
| Model Type | Instruction-tuned Language Model |
What is Meta-Llama-3.1-8B-Instruct-GGUF?
This is a quantized version of Meta's LLaMA 3.1 8B instruction-tuned language model, converted into various GGUF formats for efficient deployment. The model supports multiple quantization levels ranging from 32GB (F32) down to 2.95GB (IQ2_M), allowing users to balance performance and resource requirements.
Implementation Details
The model uses llama.cpp for quantization and offers multiple GGUF variants optimized for different hardware configurations. It implements a specific prompt format with system, user, and assistant roles, and includes cutting-edge knowledge up to December 2023.
- Multiple quantization options (Q8_0 to IQ2_M)
- Optimized variants for ARM chips and AVX2/AVX512 CPUs
- Special quantizations for GPU acceleration (cuBLAS/rocBLAS)
Core Capabilities
- Multilingual support across 8 languages
- Instruction-following and conversational abilities
- Efficient deployment options for various hardware configurations
- Memory-efficient quantization options for resource-constrained environments
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its extensive range of quantization options, making it highly adaptable to different hardware configurations while maintaining performance. It's particularly notable for including specialized quantizations for ARM processors and modern CPU architectures.
Q: What are the recommended use cases?
The model is ideal for deployment in production environments where resource optimization is crucial. For maximum quality, users should choose Q6_K_L or Q5_K_L variants, while those with limited resources can opt for the IQ3_XS or IQ2_M variants that still maintain reasonable performance.
