Codeup 13B - Details

Codeup 13B is a large language model developed by Deepse, a non-profit organization. With 13b parameters, it is designed for efficient instruction tuning and optimized for multilingual coding tasks. The model's licensing details are not specified.

Codeup 13B is a multilingual code generation model based on Llama2, optimized for code-specific tasks with parameter-efficient instruction-tuning. It leverages high-quality instruction-following data and techniques like LoRA to adapt pre-trained models without full parameter updates. The model is trained on filtered datasets to enhance programming language understanding and supports efficient deployment on a single RTX 3090. Its focus on code generation and multilingual capabilities makes it suitable for diverse coding applications.

Codeup 13B is a large language model with 13b parameters, placing it in the mid-scale category, offering balanced performance for moderate complexity tasks. Its 4k context length is suitable for short tasks but limited for long texts, making it efficient for focused coding applications. The model’s parameter size allows for effective instruction tuning without excessive resource demands, while its context length supports concise coding workflows.

• Parameter Size: 13b – mid-scale models provide balanced performance for moderate complexity.
• Context Length: 4k – short contexts are efficient for short tasks but limited for long texts.

Codeup 13B is a model designed for code generation, code completion, and multilingual code support, with potential applications in software development, programming education, and cross-language coding tasks. Possible uses could include assisting developers in writing code across multiple programming languages, automating repetitive coding tasks, or supporting collaborative projects that require multilingual code integration. Possible applications might also extend to creating code snippets, debugging, or generating documentation tailored to specific programming contexts. However, these possible uses require thorough investigation to ensure alignment with specific needs and constraints. The model’s focus on instruction-following and parameter-efficient tuning suggests it could be adapted for specialized coding workflows, but further testing would be necessary to confirm its effectiveness in real-world scenarios.

• Intended Uses: code generation, code completion, multilingual code support

Codeup 13B is a model with potential applications in areas such as code generation, code completion, and multilingual code support, where its design could enable possible uses in software development workflows, programming education tools, or collaborative coding environments. Possible applications might include automating code snippets for specific programming languages, enhancing multilingual code integration in projects, or supporting developers in debugging tasks through instruction-following capabilities. Possible uses could also extend to generating documentation or adapting code across different programming paradigms, though these possibilities require further exploration. Each potential application must be thoroughly evaluated and tested before deployment to ensure alignment with specific requirements and constraints.

• Possible Applications: code generation, code completion, multilingual code support

Codeup 13B in its medium q4 version requires a GPU with at least 20GB VRAM, such as an RTX 3090, to balance precision and performance efficiently. This version is suitable for systems with a multi-core CPU, 32GB+ RAM, and adequate cooling to handle the model’s 13B parameters. Possible hardware constraints may arise for lower-end GPUs, so users should verify their system’s capabilities.

• fp16, q2, q3, q4, q5, q6, q8

Codeup 13B is a 13b-parameter large language model optimized for multilingual coding tasks with efficient instruction tuning, designed to support code generation, completion, and cross-language development. Its quantized versions, including q4, allow flexible deployment across hardware configurations while maintaining performance balance.

Huggingface Model Page
Ollama Model Page