WizardLM-Uncensored-SuperCOT-StoryTelling-30b
Maintainer: Monero
45
🏋️
| 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
WizardLM-Uncensored-SuperCOT-StoryTelling-30b is a large language model developed by Monero, a creator on the Hugging Face platform. It is a triple model merge, combining WizardLM Uncensored, SuperCOT, and Storytelling capabilities. This results in a comprehensive boost in reasoning and story writing abilities compared to the individual models.
Model inputs and outputs
WizardLM-Uncensored-SuperCOT-StoryTelling-30b is a text-to-text model, capable of generating text based on provided prompts.
Inputs
- Text prompts that can cover a wide range of topics, from open-ended questions to creative writing tasks.
Outputs
- Coherent and contextually-relevant text responses, ranging from factual information to imaginative storytelling.
Capabilities
The model excels at tasks that require strong language understanding, reasoning, and generation capabilities. It can engage in open-ended conversations, answer questions, and produce creative narratives on a variety of subjects. The incorporation of Uncensored, COT, and Storytelling capabilities makes it a powerful tool for tasks such as creative writing, analysis, and open-ended problem-solving.
What can I use it for?
WizardLM-Uncensored-SuperCOT-StoryTelling-30b could be useful for a wide range of applications, such as:
- Generating creative fiction and narratives
- Answering open-ended questions and providing in-depth analysis
- Assisting with research and content creation
- Engaging in open-ended conversations and task completion
Things to try
Try providing the model with prompts that require a balance of reasoning, analysis, and creative expression. Experiment with different prompt styles, such as open-ended questions, creative writing tasks, or hypothetical scenarios, to see the breadth of the model's capabilities.
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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