Gemma-2-9B-It-SPPO-Iter3-GGUF
| Property | Value |
|---|---|
| Parameter Count | 9.24B |
| License | Gemma |
| Base Model | UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3 |
| Language | English |
What is Gemma-2-9B-It-SPPO-Iter3-GGUF?
This is a comprehensive quantization suite of the Gemma-2-9B model, optimized using llama.cpp's advanced quantization techniques. The model offers various GGUF formats ranging from 3.43GB to 36.97GB, making it adaptable to different hardware configurations and performance requirements.
Implementation Details
The model utilizes imatrix quantization with multiple precision levels, from full F32 weights to highly compressed IQ2_M format. Each variant is carefully balanced for the trade-off between model size and performance quality.
- Supports multiple quantization formats (Q8_0 to IQ2_M)
- Uses specialized prompt format with turn-based structure
- Optimized for various hardware configurations (CPU, GPU, Apple Silicon)
- Includes special quantization options for embed and output weights
Core Capabilities
- Text generation with high-quality output across different compression levels
- Efficient memory usage with multiple quantization options
- Optimized performance on different hardware architectures
- Support for conversational applications
Frequently Asked Questions
Q: What makes this model unique?
This model offers an extensive range of quantization options optimized for different hardware setups, making it highly versatile for various deployment scenarios. The imatrix quantization technique ensures optimal performance even at lower precision levels.
Q: What are the recommended use cases?
For users with high-end GPUs, the Q6_K_L or Q5_K_M variants are recommended for optimal quality. For systems with limited resources, the IQ4_XS or IQ3_M variants offer a good balance of performance and efficiency. The model is particularly suited for text generation and conversational applications.
