Instructions to use procedure2012/Aurora-Coder-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use procedure2012/Aurora-Coder-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="procedure2012/Aurora-Coder-Base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("procedure2012/Aurora-Coder-Base") model = AutoModel.from_pretrained("procedure2012/Aurora-Coder-Base") - Notebooks
- Google Colab
- Kaggle
Aurora-Coder-Base
1. Introduction
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.
2. Evaluation Results
Comprehensive Benchmark Results
| Benchmark | StarBase | CodeNova | Aurora-mini | Aurora-Coder-Base | |
|---|---|---|---|---|---|
| Core Reasoning Tasks | Math Reasoning | 0.579 | 0.535 | 0.552 | 0.592 |
| Logical Reasoning | 0.810 | 0.831 | 0.824 | 0.846 | |
| Common Sense | 0.731 | 0.734 | 0.750 | 0.761 | |
| Language Understanding | Reading Comprehension | 0.681 | 0.711 | 0.673 | 0.732 |
| Question Answering | 0.607 | 0.592 | 0.591 | 0.628 | |
| Text Classification | 0.833 | 0.808 | 0.832 | 0.843 | |
| Sentiment Analysis | 0.785 | 0.780 | 0.756 | 0.806 | |
| Generation Tasks | Code Generation | 0.676 | 0.665 | 0.642 | 0.692 |
| Creative Writing | 0.609 | 0.623 | 0.639 | 0.656 | |
| Dialogue Generation | 0.657 | 0.616 | 0.618 | 0.673 | |
| Summarization | 0.762 | 0.780 | 0.748 | 0.787 | |
| Specialized Capabilities | Translation | 0.808 | 0.778 | 0.808 | 0.816 |
| Knowledge Retrieval | 0.655 | 0.645 | 0.691 | 0.697 | |
| Instruction Following | 0.725 | 0.743 | 0.742 | 0.779 | |
| Safety Evaluation | 0.715 | 0.700 | 0.703 | 0.759 |
Overall Performance Summary
The Aurora-Coder-Base demonstrates strong performance across all evaluated benchmark categories, with particularly notable results in reasoning and generation tasks.
3. Chat Website & API Platform
We offer a chat interface and API for you to interact with Aurora-Coder-Base. Please check our official website for more details.
4. How to Run Locally
Please refer to our code repository for more information about running Aurora-Coder-Base locally.
Temperature
We recommend setting the temperature parameter to 0.6.
5. License
This repository is released under the mit license. The model supports commercial use.
6. Contact
If you have any questions, please contact us at hello@aurora.dev.
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