OpenOrca-Platypus2-13B
Maintainer: Open-Orca
226
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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 OpenOrca-Platypus2-13B model is a merge of the [object Object] and [object Object] models. It combines the strengths of the Platypus2-13B model, which was trained on a STEM and logic-based dataset, with the capabilities of the OpenOrcaxOpenChat-Preview2-13B model, which was fine-tuned on a refined subset of the OpenOrca dataset.
Model inputs and outputs
The OpenOrca-Platypus2-13B model is an auto-regressive language model based on the Llama 2 transformer architecture. It takes in text prompts as input and generates coherent and contextual text as output.
Inputs
- Text prompts of varying lengths
Outputs
- Continuation of the input text in a natural and coherent manner
- Responses to open-ended questions or instructions
Capabilities
The OpenOrca-Platypus2-13B model has demonstrated strong performance on a variety of benchmarks, including the HuggingFace Leaderboard, AGIEval, and BigBench-Hard evaluations. It consistently ranks near the top of the leaderboards for 13B models, showcasing its capabilities in areas like logical reasoning, general knowledge, and open-ended language understanding.
What can I use it for?
The OpenOrca-Platypus2-13B model can be used for a wide range of natural language processing tasks, such as:
- General-purpose language generation, including creative writing, story generation, and dialogue systems
- Question answering and information retrieval
- Logical reasoning and problem-solving
- Summarization and text comprehension
Given its strong performance on benchmarks, this model could be particularly useful for applications that require advanced language understanding and reasoning abilities, such as virtual assistants, educational tools, and scientific research.
Things to try
One interesting aspect of the OpenOrca-Platypus2-13B model is its ability to combine the strengths of its two parent models. By merging the STEM and logic-focused Platypus2-13B with the more general-purpose OpenOrcaxOpenChat-Preview2-13B, the resulting model may be able to excel at both specialized, technical tasks as well as open-ended language understanding. Prompts that require a mix of analytical and creative thinking could be a fruitful area to explore with this model.
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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