WizardLM-2-8x22B-GGUF
Maintainer: MaziyarPanahi
104
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| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
The MaziyarPanahi/WizardLM-2-8x22B-GGUF model is based on the original microsoft/WizardLM-2-8x22B model. It is a variant of the WizardLM-2 family of large language models developed by Microsoft, with files in the GGUF format for use with tools like llama.cpp. Similar models in this family include the MaziyarPanahi/WizardLM-2-7B-GGUF which has a smaller 7B parameter size.
Model inputs and outputs
The WizardLM-2-8x22B-GGUF model is a text-to-text model, taking in natural language prompts as input and generating relevant text responses as output. It can handle a wide range of tasks like answering questions, generating stories, and providing task-oriented assistance.
Inputs
- Natural language prompts: The model accepts free-form text prompts describing a task or request.
Outputs
- Generated text: The model outputs relevant text responses to complete the requested task or answer the given prompt.
Capabilities
The WizardLM-2-8x22B-GGUF model demonstrates strong performance across a variety of language understanding and generation benchmarks. It outperforms many leading open-source models in areas like complex chat, reasoning, and multilingual capabilities. The model can handle tasks like question answering, task-oriented dialogue, and open-ended text generation with a high degree of fluency and coherence.
What can I use it for?
The WizardLM-2-8x22B-GGUF model can be used for a wide range of natural language processing applications, such as:
- Chatbots and virtual assistants: The model can be used to build conversational AI agents that can engage in helpful and engaging dialogues.
- Content generation: The model can be used to generate high-quality text content like articles, stories, and product descriptions.
- Question answering: The model can be used to build systems that can answer a wide range of questions accurately and informatively.
- Task-oriented assistance: The model can be used to build AI assistants that can help users complete specific tasks like writing, coding, or math problems.
Things to try
Some interesting things to try with the WizardLM-2-8x22B-GGUF model include:
- Exploring the model's multilingual capabilities by prompting it in different languages.
- Evaluating the model's reasoning and problem-solving skills on complex tasks like mathematical word problems or coding challenges.
- Experimenting with different prompt engineering techniques to see how the model's responses can be tailored for specific use cases.
- Comparing the performance of this model to similar large language models like WizardLM-2-7B-GGUF or GPT-based models.
Overall, the WizardLM-2-8x22B-GGUF model represents a powerful and versatile text generation system that can be applied to a wide range of natural language processing tasks.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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