Meta-Llama-3.1-8B-SurviveV3-GGUF Quantizations
| Property | Value |
|---|---|
| Original Model | Meta-Llama-3.1-8B-SurviveV3 |
| Quantization Method | llama.cpp imatrix |
| Size Range | 2.95GB - 16.07GB |
| Author | bartowski |
What is lolzinventor_Meta-Llama-3.1-8B-SurviveV3-GGUF?
This is a comprehensive collection of GGUF quantizations of the Meta-Llama-3.1-8B-SurviveV3 model, created using llama.cpp's imatrix quantization method. The collection offers various compression levels to accommodate different hardware configurations and use cases, ranging from full F16 precision to highly compressed versions.
Implementation Details
The quantizations were performed using llama.cpp release b4792, featuring both traditional K-quants and newer I-quants. The model implements special handling for embed/output weights in certain variants to maintain quality while reducing size.
- Multiple quantization formats (Q8_0 through Q2_K)
- Special versions with Q8_0 embed/output weights
- New IQ formats for improved performance on specific hardware
- Online weight repacking support for ARM and AVX systems
Core Capabilities
- Flexible deployment options from 16GB to 2.95GB
- Optimized performance on various hardware architectures
- Quality-preserving compression techniques
- Compatible with llama.cpp-based projects and LM Studio
Frequently Asked Questions
Q: What makes this model unique?
This collection provides an extensive range of quantization options, allowing users to choose the optimal balance between model size, quality, and performance for their specific hardware setup. The implementation of both K-quants and I-quants, along with special handling of embed/output weights, makes it highly versatile.
Q: What are the recommended use cases?
For maximum quality, use Q6_K_L or Q6_K versions. For balanced performance, Q4_K_M is recommended as the default choice. For systems with limited RAM, the IQ3 and IQ2 variants offer surprisingly usable performance at minimal size requirements.
