Dolphincoder 15B - Details

Dolphincoder 15B is a large language model developed by the community-driven initiative Cognitive Computations, featuring 15 billion parameters. It operates under the BigCode Open Rail-M V1 License Agreement, ensuring open access and collaboration. This model specializes in coding tasks, with the 15B variant designed to excel in complex programming challenges while maintaining uncensored capabilities.

Dolphincoder 15B is a large language model developed by Cognitive Computations with 15 billion parameters, released under the BigCode Open Rail-M V1 License Agreement. It is based on StarCoder2-15b and trained on extensive coding data to excel in programming tasks. The model is uncensored and designed to be compliant, but it includes filters to remove alignment and bias. Users are advised to implement their own alignment layer for ethical considerations, as the model may generate content that could be unethical or inappropriate. Responsibility for the generated output lies with the user.

Dolphincoder 15B has 15 billion 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 16k token context length falls into the long context range, enabling it to handle extended texts effectively but requiring significant computational resources. The 15b parameter size allows for robust coding capabilities, while the 16k context length supports detailed reasoning over longer sequences, though both may demand substantial hardware for optimal use.

• Parameter Size: 15b (mid-scale, balanced performance for moderate complexity)
• Context Length: 16k (long context, ideal for extended texts but resource-intensive)

Dolphincoder 15B is a large language model designed for code generation, code translation between programming languages, and debugging and troubleshooting. Its 15 billion parameters and 16k token context length make it a possible tool for handling complex coding tasks, though its effectiveness in specific scenarios would require thorough testing. Possible uses could include assisting developers in writing code, converting code between languages like Python to JavaScript, or identifying and fixing errors in software. However, these possible applications may vary depending on the context, and users should evaluate their suitability before deployment. The model’s uncensored nature and open-source licensing also suggest it could be adapted for possible research or customization in coding-related fields.

• code generation
• code translation between programming languages
• debugging and troubleshooting

Dolphincoder 15B is a large language model with 15 billion parameters and a 16k token context length, making it a possible tool for various coding-related tasks. Possible applications could include code generation, where it might assist developers in creating code snippets or entire programs. It could also be used for code translation between programming languages, potentially helping in converting code from one language to another. Debugging and troubleshooting are other possible areas, where the model might identify errors or suggest fixes. Additionally, it could be applied to code optimization, where it might suggest improvements for efficiency. However, these possible applications require thorough evaluation and testing before deployment to ensure they meet specific needs and standards.

• code generation
• code translation between programming languages
• debugging and troubleshooting
• code optimization

Dolphincoder 15B with the medium q4 quantization requires a GPU with at least 16GB VRAM and a system with 32GB RAM to run efficiently, making it a possible option for users with mid-range hardware. This version balances precision and performance, though actual requirements may vary based on workload and optimization. Possible applications for this setup include coding tasks, but users should verify compatibility with their specific graphics card and system configuration.

• fp16, q2, q3, q4, q5, q6, q8

Dolphincoder 15B is a large language model with 15 billion parameters and a 16k token context length, developed by Cognitive Computations under the BigCode Open Rail-M V1 License Agreement, designed for coding tasks with uncensored capabilities. It emphasizes code generation, translation, and debugging but requires user-driven alignment for ethical use.

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