Apparatus_24B-GGUF
| Property | Value |
|---|---|
| Original Model | OddTheGreat/Apparatus_24B |
| Format | GGUF (Various Quantizations) |
| Size Range | 9.0GB - 25.2GB |
| Author | mradermacher |
What is Apparatus_24B-GGUF?
Apparatus_24B-GGUF is a comprehensive collection of quantized versions of the original Apparatus 24B model, optimized for different use cases and hardware configurations. This implementation offers various quantization levels that balance model size, inference speed, and quality, making the powerful 24B parameter model more accessible for different computational resources.
Implementation Details
The model comes in multiple quantization formats, each optimized for different use cases:
- Q2_K: Smallest size at 9.0GB, suitable for limited resources
- Q4_K_S/M: Fast and recommended versions at 13.6GB/14.4GB
- Q6_K: Very good quality at 19.4GB
- Q8_0: Highest quality option at 25.2GB
- IQ4_XS: Specialized quantization at 13.0GB
Core Capabilities
- Multiple quantization options for different hardware capabilities
- Optimized performance-to-size ratios
- Fast inference with recommended Q4_K variants
- High-quality output with Q6_K and Q8_0 variants
- Compatible with standard GGUF loaders
Frequently Asked Questions
Q: What makes this model unique?
This implementation stands out for its diverse range of quantization options, allowing users to choose the perfect balance between model size, speed, and quality for their specific needs. The availability of both standard and IQ-quants provides additional flexibility.
Q: What are the recommended use cases?
For most users, the Q4_K_S or Q4_K_M variants are recommended as they offer a good balance of speed and quality. For those prioritizing quality and having sufficient computational resources, the Q6_K or Q8_0 variants are ideal. Users with limited resources can opt for the Q2_K variant.
