SOLAR-10.7B Instruct V1.0 Uncensored GGUF
| Property | Value |
|---|---|
| Parameter Count | 10.7B |
| License | Apache 2.0 |
| Author | TheBloke (Quantization) / Stepan Zuev (Original) |
| Format | GGUF (Various Quantizations) |
What is SOLAR-10.7B-Instruct-v1.0-uncensored-GGUF?
SOLAR-10.7B-Instruct-v1.0-uncensored-GGUF is a quantized version of the SOLAR language model, specifically optimized for efficient deployment and inference. This model represents a significant advancement in accessible AI, offering multiple quantization options from 2-bit to 8-bit precision to balance performance and resource requirements.
Implementation Details
The model is available in various GGUF quantization formats, ranging from 4.55GB (Q2_K) to 11.41GB (Q8_0) in size. It supports GPU acceleration through llama.cpp and various integrations including text-generation-webui, KoboldCpp, and LM Studio.
- Multiple quantization options (Q2_K through Q8_0)
- GPU layer offloading support
- Compatible with major GGUF-supporting frameworks
- Optimized for both CPU and GPU inference
Core Capabilities
- Instruction-following and chat functionality
- Flexible deployment options across different hardware configurations
- Extended context length support up to 4096 tokens
- Integration with popular frameworks like LangChain
Frequently Asked Questions
Q: What makes this model unique?
This model combines the powerful SOLAR architecture with various quantization options, making it highly accessible for different hardware configurations while maintaining good performance. The uncensored version offers more flexibility in responses compared to standard versions.
Q: What are the recommended use cases?
The model is well-suited for chat applications, instruction-following tasks, and general language understanding. The Q4_K_M and Q5_K_M quantizations are recommended for optimal balance between performance and resource usage.
