
Open Orca Platypus2 13B

Open Orca Platypus2 13B is a large language model developed by the Openorca community. It features 13b parameters, making it suitable for a wide range of tasks. The model combines the strengths of OpenOrca and Platypus2-13B to deliver versatile capabilities in chat, text, and code generation. While the specific License_Name is not provided, the project is part of the open-source ecosystem.
Description of Open Orca Platypus2 13B
Open Orca Platypus2 13B is a merged model combining garage-bAInd/Platypus2-13B and Open-Orca/OpenOrcaxOpenChat-Preview2-13B, built on the Llama 2 transformer architecture. It is trained on STEM and logic-based datasets, achieving strong performance on benchmarks like MMLU (59.5), ARC (62.88), and HellaSwag (83.19). The model features instruction tuning with LoRA and is optimized for English language tasks using 1x A100-80GB hardware. Maintained by the Openorca community, it offers versatile capabilities for chat, text, and code generation.
Parameters & Context Length of Open Orca Platypus2 13B
Open Orca Platypus2 13B has 13b parameters, placing it in the mid-scale category of open-source LLMs, offering a balance between performance and resource efficiency for moderate complexity tasks. Its 4k context length falls into the short context range, making it suitable for concise interactions but limiting its ability to process extended texts. This configuration implies it prioritizes accessibility and speed over handling very long or highly complex inputs.
- Parameter Size: 13b
- Context Length: 4k
Possible Intended Uses of Open Orca Platypus2 13B
Open Orca Platypus2 13B is a versatile model with 13b parameters and a 4k context length, capable of text generation, question answering, and code generation. Possible uses include creating drafts for creative writing, assisting with general knowledge queries, or generating code snippets for programming tasks. These potential applications may vary in effectiveness depending on the specific requirements and context. Possible uses could also extend to educational tools, content creation, or exploratory coding, but further testing is needed to confirm their suitability. The model’s design suggests it could support tasks requiring logical reasoning or structured output, though its performance in these areas remains to be thoroughly evaluated.
- text generation
- question answering
- code generation
Possible Applications of Open Orca Platypus2 13B
Open Orca Platypus2 13B is a versatile model with 13b parameters and a 4k context length, making it possible to support applications like creative writing, educational content development, or general-purpose code assistance. Possible uses could include generating structured text for research, answering technical questions, or assisting with programming tasks. It is possible that the model could also be used for exploratory analysis or drafting documents, though these potential applications require further investigation. The model’s design suggests it might be suitable for tasks involving logical reasoning or structured output, but each possible use case must be thoroughly evaluated before deployment.
- text generation
- question answering
- code generation
Quantized Versions & Hardware Requirements of Open Orca Platypus2 13B
Open Orca Platypus2 13B in its medium q4 version requires a GPU with at least 16GB VRAM for efficient operation, as this quantization balances precision and performance. This setup is possible for systems with a multi-core CPU and adequate cooling, though testing on specific hardware is essential. The model’s q4 version is designed to reduce resource demands compared to higher-precision variants like fp16, making it a possible choice for users with mid-range GPUs. However, performance may vary depending on the workload and system configuration.
- fp16, q2, q3, q4, q5, q6, q8
Conclusion
Open Orca Platypus2 13B is a 13b parameter model with a 4k context length, designed for versatile tasks like text, question answering, and code generation. It combines OpenOrca and Platypus2-13B, leveraging Llama 2 architecture and STEM-focused training for strong performance on benchmarks, while being optimized for English tasks and community-driven development.