Cakrawala-8B-i1-GGUF
| Property | Value |
|---|---|
| Parameter Count | 8.03B |
| License | MIT |
| Author | mradermacher |
| Base Model | NarrativAI/Cakrawala-8B |
What is Cakrawala-8B-i1-GGUF?
Cakrawala-8B-i1-GGUF is a quantized version of the NarrativAI/Cakrawala-8B model, specifically optimized using imatrix quantization techniques. This model comes in various compression formats ranging from 2.1GB to 6.7GB, offering different trade-offs between size, speed, and quality.
Implementation Details
The model utilizes advanced quantization techniques, particularly the imatrix (i1) approach, to create multiple variants suitable for different deployment scenarios. The quantization options range from lightweight IQ1_S (2.1GB) for resource-constrained environments to high-quality Q6_K (6.7GB) for optimal performance.
- Multiple quantization variants (IQ1 through Q6_K)
- Optimized for different hardware configurations (ARM, SVE)
- Includes special optimizations for specific architectures (i8mm, sve)
Core Capabilities
- Efficient deployment with various size/quality trade-offs
- Conversational AI applications
- Supports English language processing
- Compatible with transformers library
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 balance between model size and performance for their specific use case. The imatrix quantization technique provides superior quality compared to traditional quantization methods.
Q: What are the recommended use cases?
For optimal performance with reasonable size requirements, the Q4_K_M variant (5.0GB) is recommended. For resource-constrained environments, the IQ2_M variant (3.0GB) offers a good balance between size and quality. The Q6_K variant (6.7GB) is ideal for scenarios requiring maximum quality.
