EVA-Tissint v1.2 14B GGUF
| Property | Value |
|---|---|
| Parameter Count | 14.8B |
| Model Type | Transformer |
| Format | GGUF |
| Language | English |
What is EVA-Tissint-v1.2-14B-GGUF?
EVA-Tissint v1.2 14B GGUF is a quantized version of the original EVA-Tissint language model, optimized for efficient deployment and reduced memory footprint while maintaining performance. This version offers multiple quantization options ranging from 5.9GB to 15.8GB, allowing users to balance between model size and quality based on their requirements.
Implementation Details
The model implements various quantization techniques, including standard and improved quantization (IQ) methods. It provides 12 different quantization variants, with file sizes ranging from Q2_K (5.9GB) to Q8_0 (15.8GB). The implementation focuses on maintaining model quality while reducing the resource requirements for inference.
- Multiple quantization options for different use-cases
- Improved Quantization (IQ) variants available
- Optimized for both x86 and ARM architectures
- Compatible with standard GGUF loaders
Core Capabilities
- Conversational AI applications
- Text generation and processing
- Flexible deployment options with various quantization levels
- Cross-platform compatibility
Frequently Asked Questions
Q: What makes this model unique?
The model's standout feature is its range of quantization options, particularly the recommended Q4_K_S and Q4_K_M variants that offer an optimal balance between size and performance. The availability of IQ-quants also provides superior quality compared to similar-sized non-IQ variants.
Q: What are the recommended use cases?
For most users, the Q4_K_S (8.7GB) or Q4_K_M (9.1GB) variants are recommended for their balance of speed and quality. For highest quality requirements, the Q8_0 variant is recommended, while resource-constrained environments might benefit from the smaller Q2_K or Q3_K_S variants.
