Zephyr Orpo 141b A35b V0.1 GGUF
Zephyr Orpo 141b A35b V0.1 GGUF is an AI model that combines speed and efficiency. It's a Mixture of Experts (MoE) model with 141 billion total parameters and 35 billion active parameters. Fine-tuned on a mix of publicly available and synthetic datasets, it's primarily designed for English language tasks. What makes it remarkable is its ability to process information quickly, with a load time of 11.67 seconds and a sample time of 0.04 milliseconds per token. This allows it to handle tasks like building a website in 10 simple steps, as demonstrated in its example output. Its performance is further highlighted by its ability to generate 25,894 tokens per second. While its capabilities are impressive, it's essential to note that its performance may vary depending on the task and input.
Table of Contents
Model Overview
Meet the Zephyr-orpo-141b-A35b-v0.1 model, a fine-tuned language model designed to assist with various tasks. This model is a type of Mixture of Experts (MoE) model, which means it’s made up of many smaller models that work together to generate human-like text.
Key Attributes
- Large and in charge: This model has a whopping
141Btotal parameters and35Bactive parameters. - English expert: The model is primarily trained on English language data, making it perfect for tasks that require a strong understanding of English.
- Open-source: The model is licensed under Apache 2.0, which means it’s free to use and modify.
How it Works
The model was fine-tuned on a mix of publicly available and synthetic datasets. This diverse range of texts helps it generate more accurate and informative responses.
Example Use Case
Want to build a website? The model can guide you through the process in 10 simple steps. Just ask it a question, and it’ll respond with a helpful answer.
Performance Metrics
| Metric | Value |
|---|---|
| Load time | 11,670.53 ms |
| Sample time | 16.30 ms per token |
| Prompt eval time | 65.19 ms per token |
| Eval time | 662.84 ms per token |
| Total time | 284,314.00 ms per 499 tokens |
Capabilities
The Zephyr-orpo-141b-A35b-v0.1 model is a powerful AI assistant that can help with a wide range of tasks.
Primary Tasks
- Answering questions
- Generating text
- Providing step-by-step instructions
- Offering helpful advice
Strengths
- Knowledge base: The model has been fine-tuned on a mix of publicly available and synthetic datasets, giving it a broad knowledge base to draw from.
- Language understanding: The model is primarily trained on English, but it can understand and respond to a wide range of questions and prompts.
- Conversational flow: The model is designed to engage in natural-sounding conversations, making it feel like you’re talking to a real person.
Unique Features
- Mixture of Experts (MoE) model: The model uses a MoE architecture, which allows it to draw on the strengths of multiple models to generate more accurate and informative responses.
- Large parameter count: With
141Btotal parameters and35Bactive parameters, the model has a huge capacity for learning and generating complex text.
Performance
The Zephyr-orpo-141b-A35b-v0.1 model showcases remarkable performance in various tasks, making it a robust and efficient tool for natural language processing.
Speed
How fast can a model respond to a user’s query? The Zephyr-orpo-141b-A35b-v0.1 model demonstrates impressive speed, with a sample time of 16.30 ms per token.
Accuracy
But speed is not the only factor; accuracy is also crucial. The Zephyr-orpo-141b-A35b-v0.1 model achieves high accuracy in its responses, as seen in the example conversation.
Efficiency
Efficiency is another key aspect of the Zephyr-orpo-141b-A35b-v0.1 model. With a total of 141B parameters, the model is able to process large amounts of data while maintaining a relatively low active parameter count of 35B.
Limitations
The Zephyr-orpo-141b-A35b-v0.1 model is a powerful tool, but it’s not perfect. Let’s talk about some of its limitations.
Limited Domain Knowledge
The model is primarily fine-tuned on English language datasets. This means it might not perform well on tasks that require knowledge of other languages or domains.
Dependence on Data Quality
The model is only as good as the data it’s trained on. If the training data contains biases or inaccuracies, the model may learn and reproduce these flaws.
Complexity and Nuance
The model can struggle with complex or nuanced tasks, such as understanding sarcasm, humor, or figurative language.
Format
The Zephyr-orpo-141b-A35b-v0.1 model is a Mixture of Experts (MoE) model with a whopping 141B total parameters and 35B active parameters.
Architecture
The model uses a sharded architecture, which means it’s split into multiple files that need to be loaded together.
Input Format
The model accepts input in the form of text prompts, which need to be formatted in a specific way.
Output Format
The model outputs text responses, which can be quite long and detailed.
Special Requirements
To use this model, you’ll need to have the llama.cpp library installed, and you’ll need to use the llama_load_model_from_file function to load the model.
