Llama-3.1-Tulu-3-8B-abliterated-GGUF
| Property | Value |
|---|---|
| Parameter Count | 8.03B |
| License | LLaMA 3.1 |
| Base Model | huihui-ai/Llama-3.1-Tulu-3-8B-abliterated |
| Language | English |
What is Llama-3.1-Tulu-3-8B-abliterated-GGUF?
This is a quantized version of the Llama-3.1-Tulu-3-8B model, optimized for efficient deployment while maintaining performance. It offers multiple quantization options ranging from 3.3GB to 16.2GB, allowing users to balance between model size and quality based on their requirements.
Implementation Details
The model provides various quantization formats, with the most notable being Q4_K_S and Q4_K_M, which are recommended for their optimal balance of speed and quality. The implementation includes specialized formats like IQ4_XS for enhanced efficiency and Q8_0 for maximum quality.
- Multiple quantization options from Q2_K (3.3GB) to f16 (16.2GB)
- Optimized for different hardware configurations
- Includes special arm-optimized versions
- Features both standard and IQ (Integer Quantization) variants
Core Capabilities
- Efficient inference with various memory footprints
- Uncensored text generation capabilities
- Optimized for conversational applications
- Compatible with standard GGUF loaders
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its variety of quantization options, allowing users to choose the perfect balance between model size and performance. It's particularly notable for including both standard and IQ quantization variants, with specific optimizations for different hardware architectures.
Q: What are the recommended use cases?
The model is ideal for applications requiring efficient deployment of LLaMA 3.1 capabilities. The Q4_K_S and Q4_K_M variants are recommended for general use, while Q8_0 is suggested for scenarios requiring maximum quality. The Q4_0_4_4 variant is specifically optimized for ARM processors.
