How to use from the
Use from the
Transformers library
# 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", device_map="auto")
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Aurora-Coder-Base

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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