Stable Code 3B - Details

Stable Code 3B is a large language model developed by Stability-Ai, featuring 3 billion parameters. It operates under the Stability AI Non-Commercial Research Community License Agreement (STABILITY-AI-NCRCLA). The model specializes in code completion tasks and supports the Fill in Middle capability, making it a valuable tool for developers and researchers in the code generation domain.

A 2.7B parameter decoder-only language model pre-trained on 1.3 trillion tokens of diverse textual and code datasets. It supports 18 programming languages selected from the 2023 StackOverflow Developer Survey and achieves state-of-the-art performance on the MultiPL-E metrics across multiple languages using BigCode's Evaluation Harness. The model is designed for code-related tasks with a focus on multilingual and large-scale code understanding.

Stable Code 3B is a 3b parameter model with a 16k context length, positioning it in the small to mid-scale category for parameters and long contexts. The 3b parameter size ensures fast and resource-efficient performance, ideal for tasks requiring moderate complexity without excessive computational demands. A 16k context length allows the model to handle extended sequences, making it suitable for complex code analysis and generation tasks that require understanding broader contextual information. This combination balances efficiency and capability, offering flexibility for developers and researchers.

• Parameter Size: 3b
• Context Length: 16k

Stable Code 3B is a 3b parameter model with a 16k context length, designed for tasks requiring code-related expertise. Possible applications include application-specific fine-tuning, where the model could be adapted to specialized domains, though further testing would be needed to confirm effectiveness. Possible uses in code generation and code completion might support developers in writing or refining code, but these scenarios would require validation to ensure accuracy and relevance. The model’s architecture suggests it could handle complex coding tasks, but possible limitations in scalability or domain specificity remain to be explored. Possible integration into development workflows or educational tools could be investigated, though thorough evaluation would be essential.

• application-specific fine-tuning
• code generation
• code completion

Stable Code 3B is a 3b parameter model with a 16k context length, offering possible applications in areas like application-specific fine-tuning, where it could be adapted to niche coding tasks, though possible limitations in domain specificity would require further exploration. Possible uses in code generation and code completion might assist developers in automating repetitive coding tasks, but possible variations in accuracy or context handling would need validation. Possible integration into educational tools for teaching programming concepts could also be considered, though possible effectiveness in diverse learning environments remains to be tested. These possible applications highlight the model’s flexibility but underscore the need for rigorous evaluation before deployment.

• application-specific fine-tuning
• code generation
• code completion

Stable Code 3B in its q4 version offers a medium balance between precision and performance, requiring a GPU with at least 12GB VRAM and 32GB system RAM for efficient operation. This configuration ensures compatibility with many modern GPUs while maintaining reasonable computational accuracy. Possible variations in performance may depend on the specific workload and quantization settings.

• q2, q3, q32, q4, q5, q6, q8

Stable Code 3B is a 3b parameter model with a 16k context length, designed for code-related tasks and released under the Stability AI Non-Commercial Research Community License Agreement. It balances efficiency and performance, making it suitable for code generation, completion, and application-specific fine-tuning, though further evaluation is needed for specific use cases.

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