soob3123_amoral-gemma3-12B-GGUF
| Property | Value |
|---|---|
| Original Model | soob3123/amoral-gemma3-12B |
| Quantization Framework | llama.cpp (b4896) |
| Size Range | 4.02GB - 23.54GB |
| Available Formats | Multiple GGUF variants |
What is soob3123_amoral-gemma3-12B-GGUF?
This is a comprehensive collection of GGUF quantized versions of the amoral-gemma3-12B model, optimized using llama.cpp's imatrix quantization technology. The collection offers various compression levels to accommodate different hardware configurations and performance requirements, ranging from full BF16 precision (23.54GB) to highly compressed IQ2_S format (4.02GB).
Implementation Details
The model implements a specialized prompt format and offers multiple quantization variants optimized for different use cases. Each variant uses imatrix quantization with carefully calibrated datasets to maintain optimal performance while reducing model size.
- Supports various quantization levels from BF16 to IQ2
- Features special K-L variants with Q8_0 for embed and output weights
- Implements online repacking for ARM and AVX CPU inference
- Optimized prompt format with specific turn markers
Core Capabilities
- Multiple compression options for different hardware configurations
- Specialized variants for ARM and AVX architectures
- High-quality compression maintaining model performance
- Flexible deployment options across different platforms
Frequently Asked Questions
Q: What makes this model unique?
The model offers an extensive range of quantization options using state-of-the-art techniques, including special variants with Q8_0 embed/output weights and new IQ formats for optimal performance on different hardware.
Q: What are the recommended use cases?
For most users, the Q4_K_M (7.30GB) variant is recommended as a balanced option. Users with limited RAM should consider Q3_K variants, while those requiring maximum quality should opt for Q6_K_L or higher variants.
