Zephyr ORPO 141B GGUF
| Property | Value |
|---|---|
| Parameter Count | 141B (35B active) |
| Model Type | Mixture of Experts (MoE) |
| License | Apache 2.0 |
| Base Model | Mixtral-8x22B-v0.1 |
| Quantization Options | 2-bit to 16-bit precision |
What is zephyr-orpo-141b-A35b-v0.1-GGUF?
This model represents a significant advancement in efficient language model deployment, offering a quantized version of the Zephyr ORPO 141B model. Built upon the Mixtral-8x22B architecture, it employs a Mixture of Experts approach with 141B total parameters while maintaining only 35B active parameters during inference.
Implementation Details
The model has been optimized through GGUF quantization, offering multiple precision options from 2-bit to 16-bit to balance performance and resource usage. It's specifically designed for English language tasks and has been fine-tuned on publicly available synthetic datasets.
- Supports various quantization levels (Q2_K through Q16_K)
- Implements efficient model sharding for improved memory management
- Provides straightforward integration with llama.cpp
Core Capabilities
- Advanced text generation and completion
- Conversational AI applications
- Flexible deployment options through different quantization levels
- Efficient inference with reduced memory footprint
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its implementation of the Mixture of Experts architecture combined with flexible quantization options, allowing users to balance performance and resource usage according to their needs. With 141B total parameters but only 35B active parameters, it provides efficient scaling while maintaining strong performance.
Q: What are the recommended use cases?
The model is particularly well-suited for English language text generation tasks, conversational AI applications, and scenarios where efficient deployment of large language models is crucial. Its various quantization options make it adaptable to different hardware constraints and performance requirements.
