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OpenCoder: A True Open-Source Approach to Code LLMs

Nov 11, 2024 - medium.com
OpenCoder is a Large Language Model (LLM) designed to understand and generate programming code, aiding in tasks such as writing, completing, or explaining code snippets. It is an open and fully transparent code language model, aiming to match the performance of top-tier proprietary and open-source models. OpenCoder also provides access to final models, tools, and shares its full training process, including data steps and protocols. Examples of other open code LLMs include Qwen from Alibaba and LlamaCode from Meta.

OpenCoder consists of two models: a smaller 1.5 billion parameter model and a larger 8 billion parameter model. It is trained on 2.5 trillion tokens, with 90% raw code and 10% code-related web data. Unlike proprietary models, OpenCoder does not keep its methods or results behind closed doors. The full release includes model weights and inference code, reproducible training data, a transparent data processing pipeline, and experimental results of ablation studies.

Key takeaways:

  • OpenCoder is an open and reproducible Large Language Model (LLM) specifically trained to understand and generate programming code.
  • It is fully transparent and aims to match the performance of top-tier proprietary and Open Source models.
  • OpenCoder comprises two models: a smaller 1.5 billion parameter model and a larger 8 billion parameter model, trained on 2.5 trillion tokens.
  • The full release of OpenCoder includes model weights and inference code, reproducible training data, a transparent data processing pipeline, and experimental results of ablation studies.
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