deepseek-coder-1.3b-base
Maintainer: deepseek-ai
57
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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
deepseek-coder-1.3b-base is a 1.3 billion parameter AI model developed by deepseek-ai that is specialized in code generation and completion. It was trained from scratch on 2 trillion tokens, with 87% of the data being code and the remaining 13% being natural language data in both English and Chinese. Compared to the deepseek-coder-33b-base and deepseek-coder-6.7b-base models, the 1.3 billion parameter version is more lightweight and accessible, while still providing state-of-the-art performance on multiple programming language benchmarks.
Model inputs and outputs
deepseek-coder-1.3b-base is a causal language model that takes in natural language or partial code as input and generates relevant text or code as output. The model can be used for a variety of code-related tasks, including code completion, code generation, and even repository-level code completion.
Inputs
- Natural language prompts or partial code snippets
Outputs
- Completed code snippets or generated code based on the input prompt
Capabilities
deepseek-coder-1.3b-base has demonstrated strong capabilities in code generation and completion, achieving state-of-the-art performance on benchmarks like HumanEval, MultiPL-E, MBPP, DS-1000, and APPS. The model is able to understand and generate code in multiple programming languages, and can even complete complex, multi-line code segments based on partial inputs.
What can I use it for?
The deepseek-coder-1.3b-base model can be a powerful tool for developers and data scientists looking to streamline their coding workflows. Some potential use cases include:
- Generating boilerplate code or scaffolding for new projects
- Completing partially written code snippets to save time
- Generating code to implement specific algorithms or functionality
- Assisting with code refactoring and optimization
- Aiding in the onboarding of new developers by providing example code
Things to try
One interesting capability of deepseek-coder-1.3b-base is its ability to perform "repository-level" code completion, where the model can generate relevant code based on the context of an entire codebase, rather than just a single code snippet. This can be particularly useful for tasks like implementing common design patterns or integrating third-party libraries into a project.
Another aspect to explore is the model's performance on domain-specific coding tasks, such as data analysis, machine learning, or web development. The model's strong natural language understanding may enable it to generate high-quality code for a variety of use cases beyond general-purpose programming.
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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