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  1. README.md +68 -0
  2. config.json +6 -0
  3. figures/fig1.png +0 -0
  4. figures/fig2.png +0 -0
  5. pytorch_model.bin +3 -0
README.md ADDED
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+ ---
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+ license: mit
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+ library_name: transformers
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+ ---
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+ # Aurora-Coder-Base
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+ <!-- markdownlint-disable first-line-h1 -->
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+ <!-- markdownlint-disable html -->
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+ <!-- markdownlint-disable no-duplicate-header -->
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+
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+ <div align="center">
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+ <img src="figures/fig1.png" width="60%" alt="Aurora-Coder-Base" />
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+ </div>
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+ <hr>
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+
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+ <div align="center" style="line-height: 1;">
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+ <a href="LICENSE" style="margin: 2px;">
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+ <img alt="License" src="figures/fig2.png" style="display: inline-block; vertical-align: middle;"/>
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+ </a>
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+ </div>
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+
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+ ## 1. Introduction
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+
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+ Aurora-Coder-Base is a code-specialised checkpoint fine-tuned on a deduplicated multi-language corpus. It targets repository-level code completion and agentic tool use.
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+
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+ ## 2. Evaluation Results
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+
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+ ### Comprehensive Benchmark Results
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+
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+ <div align="center">
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+
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+ | | Benchmark | StarBase | CodeNova | Aurora-mini | Aurora-Coder-Base |
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+ |---|---|---|---|---|---|
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+ | **Core Reasoning Tasks** | Math Reasoning | 0.579 | 0.535 | 0.552 | 0.592 |
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+ | | Logical Reasoning | 0.810 | 0.831 | 0.824 | 0.846 |
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+ | | Common Sense | 0.731 | 0.734 | 0.750 | 0.761 |
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+ | **Language Understanding** | Reading Comprehension | 0.681 | 0.711 | 0.673 | 0.732 |
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+ | | Question Answering | 0.607 | 0.592 | 0.591 | 0.628 |
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+ | | Text Classification | 0.833 | 0.808 | 0.832 | 0.843 |
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+ | | Sentiment Analysis | 0.785 | 0.780 | 0.756 | 0.806 |
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+ | **Generation Tasks** | Code Generation | 0.676 | 0.665 | 0.642 | 0.692 |
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+ | | Creative Writing | 0.609 | 0.623 | 0.639 | 0.656 |
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+ | | Dialogue Generation | 0.657 | 0.616 | 0.618 | 0.673 |
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+ | | Summarization | 0.762 | 0.780 | 0.748 | 0.787 |
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+ | **Specialized Capabilities** | Translation | 0.808 | 0.778 | 0.808 | 0.816 |
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+ | | Knowledge Retrieval | 0.655 | 0.645 | 0.691 | 0.697 |
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+ | | Instruction Following | 0.725 | 0.743 | 0.742 | 0.779 |
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+ | | Safety Evaluation | 0.715 | 0.700 | 0.703 | 0.759 |
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+
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+ </div>
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+
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+ ### Overall Performance Summary
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+ The Aurora-Coder-Base demonstrates strong performance across all evaluated benchmark categories, with particularly notable results in reasoning and generation tasks.
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+
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+ ## 3. Chat Website & API Platform
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+ We offer a chat interface and API for you to interact with Aurora-Coder-Base. Please check our official website for more details.
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+
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+ ## 4. How to Run Locally
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+
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+ Please refer to our code repository for more information about running Aurora-Coder-Base locally.
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+
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+ ### Temperature
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+ We recommend setting the temperature parameter to 0.6.
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+
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+ ## 5. License
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+ This repository is released under the mit license. The model supports commercial use.
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+
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+ ## 6. Contact
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+ If you have any questions, please contact us at hello@aurora.dev.
config.json ADDED
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+ {
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+ "model_type": "bert",
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+ "architectures": [
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+ "BertModel"
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+ ]
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+ }
figures/fig1.png ADDED
figures/fig2.png ADDED
pytorch_model.bin ADDED
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+ size 23