L3.3-Electra-R1-70b-GGUF
| Property | Value |
|---|---|
| Base Model | Steelskull/L3.3-Electra-R1-70b |
| Parameters | 70 billion |
| Format | GGUF |
| Author | ddh0 |
| Repository | Hugging Face |
What is L3.3-Electra-R1-70b-GGUF?
L3.3-Electra-R1-70b-GGUF is a collection of quantized versions of the Steelskull/L3.3-Electra-R1-70b model, specifically optimized for efficient deployment while maintaining performance. The model uses GGUF format and offers multiple quantization levels to balance between model size and quality.
Implementation Details
The model implements various imatrix quantizations, using the same calibration data as Bartowski. The quantizations are arranged in order of increasing quality, from IQ2_M to Q8_0, providing users with flexibility in choosing the right balance between model size and performance.
- Multiple quantization options: IQ2_M, IQ3_XS, IQ3_M, Q4_K_S, IQ4_XS, Q4_K_M, Q5_K_S, Q5_K_M, Q6_K, Q8_0
- GGUF format implementation for improved compatibility
- Calibrated using proven calibration data
- Includes both calibration data and imatrix
Core Capabilities
- Flexible deployment options with multiple quantization levels
- Optimized for resource-efficient inference
- Maintains model quality while reducing size
- Compatible with modern GGUF-supported frameworks
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its comprehensive range of quantization options, allowing users to choose the optimal trade-off between model size and performance. The use of GGUF format and proven calibration data ensures reliability and compatibility.
Q: What are the recommended use cases?
The model is ideal for deployment scenarios where resource optimization is crucial. The various quantization options make it suitable for different hardware configurations, from resource-constrained environments (using lighter quantizations like IQ2_M) to high-performance systems (using Q8_0).
