stable-code-instruct-3b-GGUF
| Property | Value |
|---|---|
| Original Model | stable-code-instruct-3b |
| Quantization Framework | llama.cpp (b2440) |
| Author | bartowski |
What is stable-code-instruct-3b-GGUF?
This is a collection of quantized versions of the stable-code-instruct-3b model, optimized for different use cases and hardware constraints. The quantizations range from extremely high quality (Q8_0) to minimal size (Q2_K), offering users flexibility in choosing between performance and resource usage.
Implementation Details
The model uses GGUF format and offers 16 different quantization variants, each optimized for specific use cases. The quantization levels range from Q8_0 (2.97GB) to Q2_K (1.08GB), with various intermediate options providing different quality-size tradeoffs.
- Q8_0: Highest quality quantization at 2.97GB
- Q6_K: Recommended version offering near-perfect quality at 2.29GB
- Q5 variants: High-quality options ranging from 1.94GB to 1.99GB
- Q4 variants: Good quality options with reasonable size (1.60GB-1.70GB)
- IQ4 variants: New quantization method with good performance
- Q3/IQ3 variants: Lower quality options for constrained environments
Core Capabilities
- Multiple quantization options for different hardware constraints
- Optimized performance-to-size ratios
- Compatible with llama.cpp framework
- Suitable for various deployment scenarios from high-end to resource-constrained environments
Frequently Asked Questions
Q: What makes this model unique?
This model provides a comprehensive range of quantization options for the stable-code-instruct-3b model, allowing users to choose the optimal balance between model quality and resource usage for their specific use case.
Q: What are the recommended use cases?
For most users, the Q6_K variant (2.29GB) is recommended as it offers near-perfect quality. For resource-constrained environments, the Q4_K_M or IQ4_NL variants provide a good balance of quality and size. The Q8_0 variant is ideal for users requiring maximum quality regardless of size.
