WizardLM-2-8x22B
Maintainer: alpindale
326
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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 WizardLM-2-8x22B is a large language model developed by the WizardLM@Microsoft AI team. It is a Mixture of Experts (MoE) model with 141B parameters, trained on a multilingual dataset. This model demonstrates highly competitive performance compared to leading proprietary models, and consistently outperforms existing state-of-the-art open-source models according to the maintainer's description. The WizardLM-2-7B and WizardLM-2-70B are other models in the WizardLM-2 family, each with their own unique capabilities.
Model inputs and outputs
The WizardLM-2-8x22B is a text-to-text model, meaning it takes text as input and generates text as output. It can handle a wide range of natural language processing tasks such as chatbots, language translation, and question answering.
Inputs
- Text prompts
Outputs
- Generated text
Capabilities
The WizardLM-2-8x22B demonstrates highly competitive performance on complex chat, multilingual, reasoning and agent tasks compared to leading proprietary models, according to the maintainer. It outperforms existing state-of-the-art open-source models on a range of benchmarks.
What can I use it for?
The WizardLM-2-8x22B can be used for a variety of natural language processing tasks, such as building chatbots, language translation systems, question-answering systems, and even creative writing assistants. Given its strong performance on reasoning and agent tasks, it could also be used for decision support or task automation.
Things to try
Some interesting things to try with the WizardLM-2-8x22B model could include:
- Exploring its multilingual capabilities by testing it on prompts in different languages
- Evaluating its performance on open-ended reasoning tasks that require complex logical thinking
- Experimenting with fine-tuning the model on specialized datasets to adapt it for domain-specific applications
Overall, the WizardLM-2-8x22B appears to be a powerful and versatile language model that could be useful for a wide range of natural language processing projects.
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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microsoft_WizardLM-2-7B
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WizardLM-2 7B is a powerful large language model developed by WizardLM@Microsoft AI. It is part of the WizardLM-2 family, which includes three cutting-edge models: WizardLM-2 8x22B, WizardLM-2 70B, and WizardLM-2 7B. These models demonstrate highly competitive performance compared to leading proprietary works and consistently outperform existing state-of-the-art open-source models. Model inputs and outputs WizardLM-2 7B is a multilingual model that can handle a variety of input formats, including natural language text, code, and mathematical expressions. It can generate human-like text, answer questions, summarize content, and assist with a wide range of tasks. Inputs Natural language text in multiple languages Code in various programming languages Mathematical expressions and problems Outputs Coherent and contextually appropriate text responses Answers to questions Summaries of input text Code generation and explanation Solutions to mathematical problems Capabilities WizardLM-2 7B has demonstrated strong performance on complex chat, multilingual, reasoning, and agent tasks. It outperforms many larger open-source models and even rivals advanced proprietary models in some domains. What can I use it for? WizardLM-2 7B can be used for a wide range of applications, including content creation, language translation, code generation, educational assistance, and task automation. It can be particularly useful for companies looking to enhance their natural language processing capabilities or develop intelligent chatbots and virtual assistants. Things to try One interesting aspect of WizardLM-2 7B is its ability to engage in open-ended conversation and provide nuanced, context-aware responses. You can try using the model to have natural dialogues on a variety of topics, or to assist with complex, multi-step tasks that require reasoning and problem-solving skills.
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microsoft_WizardLM-2-7B
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WizardLM-2 7B is a powerful large language model developed by WizardLM@Microsoft AI. It is part of the WizardLM-2 family, which includes three cutting-edge models: WizardLM-2 8x22B, WizardLM-2 70B, and WizardLM-2 7B. These models demonstrate highly competitive performance compared to leading proprietary works and consistently outperform existing state-of-the-art open-source models. Model inputs and outputs WizardLM-2 7B is a multilingual model that can handle a variety of input formats, including natural language text, code, and mathematical expressions. It can generate human-like text, answer questions, summarize content, and assist with a wide range of tasks. Inputs Natural language text in multiple languages Code in various programming languages Mathematical expressions and problems Outputs Coherent and contextually appropriate text responses Answers to questions Summaries of input text Code generation and explanation Solutions to mathematical problems Capabilities WizardLM-2 7B has demonstrated strong performance on complex chat, multilingual, reasoning, and agent tasks. It outperforms many larger open-source models and even rivals advanced proprietary models in some domains. What can I use it for? WizardLM-2 7B can be used for a wide range of applications, including content creation, language translation, code generation, educational assistance, and task automation. It can be particularly useful for companies looking to enhance their natural language processing capabilities or develop intelligent chatbots and virtual assistants. Things to try One interesting aspect of WizardLM-2 7B is its ability to engage in open-ended conversation and provide nuanced, context-aware responses. You can try using the model to have natural dialogues on a variety of topics, or to assist with complex, multi-step tasks that require reasoning and problem-solving skills.
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WizardLM-70B-V1.0
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WizardLM-70B-V1.0 is a large language model developed by the WizardLM Team. It is part of the WizardLM family of models, which also includes the WizardCoder and WizardMath models. The WizardLM-70B-V1.0 model was trained to follow complex instructions and demonstrates strong performance on tasks like open-ended conversation, reasoning, and math problem-solving. Compared to similar large language models, the WizardLM-70B-V1.0 exhibits several key capabilities. It outperforms some closed-source models like ChatGPT 3.5, Claude Instant 1, and PaLM 2 540B on the GSM8K benchmark, achieving an 81.6 pass@1 score, which is 24.8 points higher than the current SOTA open-source LLM. Additionally, the model achieves a 22.7 pass@1 score on the MATH benchmark, 9.2 points above the SOTA open-source LLM. Model inputs and outputs Inputs Natural language instructions and prompts**: The model is designed to accept a wide range of natural language inputs, from open-ended conversation to specific task descriptions. Outputs Natural language responses**: The model generates coherent and contextually appropriate responses to the given inputs. This can include answers to questions, elaborations on ideas, and solutions to problems. Code generation**: The WizardLM-70B-V1.0 model has also been shown to excel at code generation, with its WizardCoder variant achieving state-of-the-art performance on benchmarks like HumanEval. Capabilities The WizardLM-70B-V1.0 model demonstrates impressive capabilities across a range of tasks. It is able to engage in open-ended conversation, providing helpful and detailed responses. The model also excels at reasoning and problem-solving, as evidenced by its strong performance on the GSM8K and MATH benchmarks. One key strength of the WizardLM-70B-V1.0 is its ability to follow complex instructions and tackle multi-step problems. Unlike some language models that struggle with tasks requiring sequential reasoning, this model is able to break down instructions, generate relevant outputs, and provide step-by-step solutions. What can I use it for? The WizardLM-70B-V1.0 model has a wide range of potential applications. It could be used to power conversational AI assistants, provide tutoring and educational support, assist with research and analysis tasks, or even help with creative writing and ideation. The model's strong performance on math and coding tasks also makes it well-suited for use in STEM education, programming tools, and scientific computing applications. Developers could leverage the WizardCoder variant to build intelligent code generation and autocomplete tools. Things to try One interesting aspect of the WizardLM-70B-V1.0 model is its ability to engage in multi-turn conversations and follow up on previous context. Try providing the model with a series of related prompts and see how it maintains coherence and builds upon the discussion. You could also experiment with the model's reasoning and problem-solving capabilities by presenting it with complex, multi-step instructions or math problems. Observe how the model breaks down the task, generates intermediate steps, and arrives at a final solution. Another area to explore is the model's versatility across different domains. Test its performance on a variety of tasks, from open-ended conversation to specialized technical queries, to understand the breadth of its capabilities.
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WizardLM-13B-V1.2
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The WizardLM-13B-V1.2 model is a large pre-trained language model developed by the WizardLM team. It is a full-weight version of the WizardLM-13B model, which is based on the Llama-2 13b model. The WizardLM team has also released larger versions of the model, including the WizardLM-70B-V1.0 which slightly outperforms some closed-source LLMs on benchmarks. Model inputs and outputs The WizardLM-13B-V1.2 model is a text-to-text transformer that can be used for a variety of natural language processing tasks. It takes text prompts as input and generates relevant text responses. Inputs Text prompts or instructions for the model to follow Outputs Coherent, multi-sentence text responses that address the input prompts Capabilities The WizardLM-13B-V1.2 model is capable of following complex instructions and engaging in open-ended conversations. It has been shown to outperform other large language models on benchmarks like MT-Bench, AlpacaEval, and WizardEval. For example, the model achieves 36.6 pass@1 on the HumanEval benchmark, demonstrating its ability to generate solutions to complex coding problems. What can I use it for? The WizardLM-13B-V1.2 model could be useful for a wide range of applications that require natural language understanding and generation, such as: Engaging in open-ended conversations and answering questions Providing detailed and helpful responses to instructions and prompts Assisting with coding and software development tasks Generating human-like text for creative writing or content creation Things to try One interesting thing to try with the WizardLM-13B-V1.2 model is to provide it with complex, multi-step instructions and observe how it responds. The model's ability to follow intricate prompts and generate coherent, detailed responses is a key capability. You could also try using the model for tasks like code generation or mathematical reasoning, as the WizardLM team has shown the model's strong performance on benchmarks like HumanEval and GSM8k.
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