--- license: apache-2.0 base_model: - ByteDance-Seed/Seed-Coder-8B-Base --- # Seed-Coder-8B-Instruct ## Introduction Seed-Coder-8B-Instruct is an 8-billion-parameter model instruction-tuned specifically for code generation, code reasoning, and code understanding. It is built to empower developers with high-quality, efficient code assistance. It features: - Trained on a **massively curated corpus**, where **an LLM-based filter** is applied to select **high-quality real-world code**, **text-code alignment data**, and **synthetic datasets** — ensuring cleaner and more useful data compared to traditional heuristic-based curation. - Achieves superior performance across **code generation**, **bug fixing**, and **reasoning** tasks, rivaling or surpassing larger open-source code models. - **Instruction-tuned** to reliably follow user intents across a diverse range of coding and reasoning prompts. - Supports **long-context handling** up to 32K tokens, enabling processing of complex multi-file projects and detailed coding tasks.

## Model Downloads | Model Name | Type | Length | Download | |---------------------------------------------------------|----------|--------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | Seed-Coder-8B-Base | base | 32k | 🤗 [Hugging Face](https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Base) | | **👉Seed-Coder-8B-Instruct** | instruct | 32k | 🤗 [Hugging Face](https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Instruct) | | Seed-Coder-8B-Reasoning | reasoning | 32k | 🤗 [Hugging Face](https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Reasoning) | ## Requirements You will need to install the latest versions of `transformers` and `accelerate`: ```bash pip install -U transformers accelerate ``` ## Quickstart Here is a simple example demonstrating how to load the model and generate code using the Hugging Face `pipeline` API: ```python import transformers import torch model_id = "ByteDance-Seed/Seed-Coder-8B-Instruct" pipeline = transformers.pipeline( "text-generation", model=model_id, model_kwargs={"torch_dtype": torch.bfloat16}, device_map="auto", ) messages = [ {"role": "user", "content": "Write a quick sort algorithm."}, ] outputs = pipeline( messages, max_new_tokens=512, ) print(outputs[0]["generated_text"][-1]["content"]) ``` ## Evaluation Seed-Coder-8B-Instruct demonstrates strong performance across a variety of coding benchmarks, showing: - Competitive or superior results compared to similarly sized open-source code models. - Robustness across different programming languages and domains. - Ability to understand, reason, and repair complex code snippets. | Model | HumanEval | MBPP | MHPP | BigCodeBench (Full) | BigCodeBench (Hard) | LiveCodeBench (2410-2502) | |:-----------------------------:|:---------:|:----:|:----:|:-------------------:|:-------------------:|:-------------------------:| | CodeLlama-7B-Instruct | 40.9 | 54.0 | 6.7 | 21.9 | 3.4 | 3.6 | | DeepSeek-Coder-6.7B-Instruct | 74.4 | 74.9 | 20.0 | 35.5 | 10.1 | 9.6 | | CodeQwen1.5-7B-Chat | 83.5 | 77.7 | 17.6 | 39.6 | 18.9 | 3.0 | | Yi-Coder-9B-Chat | 82.3 | 82.0 | 26.7 | 38.1 | 11.5 | 17.5 | | Llama-3.1-8B-Instruct | 68.3 | 70.1 | 17.1 | 36.6 | 13.5 | 11.5 | | OpenCoder-8B-Instruct | 83.5 | 79.1 | 30.5 | 40.3 | 16.9 | 17.1 | | Qwen2.5-Coder-7B-Instruct | 88.4 | 82.0 | 26.7 | 41.0 | 18.2 | 17.3 | | Seed-Coder-8B-Instruct | 84.8 | 85.2 | 36.2 | 53.3 | 20.5 | 24.7 | For detailed results, please check our [📑 paper](https://arxiv.org/pdf/xxx.xxxxx). ## Citation If you find our work helpful, feel free to give us a cite. ``` @article{zhang2025seedcoder, title={Seed-Coder: Let the Code Model Curate Data for Itself}, author={Xxx}, year={2025}, eprint={2504.xxxxx}, archivePrefix={arXiv}, primaryClass={cs.CL}, url={https://arxiv.org/abs/xxxx.xxxxx}, } ```