alnrg2arg/test
alnrg2arg/test is a 10.7 billion parameter base model created by alnrg2arg, designed as a test version for pruning and quantization for on-device deployment. This model was developed by merging jeonsworld/CarbonVillain-en-10.7B-v2 and kyujinpy/Sakura-SOLAR-Instruct-DPO-v2 using mergekit. Its primary purpose is to serve as a foundation for creating highly optimized, smaller models suitable for edge computing applications.
Loading preview...
Model Overview
alnrg2arg/test is a 10.7 billion parameter base model, specifically developed by alnrg2arg as a foundational testbed for advanced model optimization techniques. The core innovation behind this model lies in its creation through the merging of two distinct models: jeonsworld/CarbonVillain-en-10.7B-v2 and kyujinpy/Sakura-SOLAR-Instruct-DPO-v2, utilizing the mergekit tool.
Key Characteristics
- Parameter Count: 10.7 billion parameters, providing a robust base for various tasks.
- Context Length: Supports a context window of 4096 tokens.
- Development Purpose: Primarily intended as an intermediate step for pruning and quantization.
Good For
- On-device Deployment: This model is explicitly designed to be pruned and quantized, making it highly suitable for applications requiring efficient, smaller models that can run directly on edge devices.
- Research in Model Merging: Offers a practical example of combining different models to potentially leverage their individual strengths.
- Optimization Workflows: Ideal for developers and researchers focused on optimizing large language models for resource-constrained environments.