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--- |
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tags: |
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- unsloth |
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- unsloth |
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license: mit |
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base_model: |
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- ByteDance-Seed/Seed-Coder-8B-Instruct |
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pipeline_tag: text-generation |
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library_name: transformers |
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--- |
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<div> |
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<p style="margin-top: 0;margin-bottom: 0;"> |
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<em><a href="https://docs.unsloth.ai/basics/unsloth-dynamic-v2.0-gguf">Unsloth Dynamic 2.0</a> achieves superior accuracy & outperforms other leading quants.</em> |
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</p> |
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<div style="display: flex; gap: 5px; align-items: center; "> |
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<a href="https://github.com/unslothai/unsloth/"> |
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<img src="https://github.com/unslothai/unsloth/raw/main/images/unsloth%20new%20logo.png" width="133"> |
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</a> |
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<a href="https://discord.gg/unsloth"> |
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<img src="https://github.com/unslothai/unsloth/raw/main/images/Discord%20button.png" width="173"> |
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</a> |
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<a href="https://docs.unsloth.ai/basics/qwen3-how-to-run-and-fine-tune"> |
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<img src="https://raw.githubusercontent.com/unslothai/unsloth/refs/heads/main/images/documentation%20green%20button.png" width="143"> |
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</a> |
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</div> |
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</div> |
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<div> |
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<p style="margin-top: 0;margin-bottom: 0;"> |
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<em><a href="https://docs.unsloth.ai/basics/unsloth-dynamic-v2.0-gguf">Unsloth Dynamic 2.0</a> achieves superior accuracy & outperforms other leading quants.</em> |
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</p> |
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<div style="display: flex; gap: 5px; align-items: center; "> |
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<a href="https://github.com/unslothai/unsloth/"> |
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<img src="https://github.com/unslothai/unsloth/raw/main/images/unsloth%20new%20logo.png" width="133"> |
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</a> |
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<a href="https://discord.gg/unsloth"> |
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<img src="https://github.com/unslothai/unsloth/raw/main/images/Discord%20button.png" width="173"> |
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</a> |
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<a href="https://docs.unsloth.ai/basics/qwen3-how-to-run-and-fine-tune"> |
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<img src="https://raw.githubusercontent.com/unslothai/unsloth/refs/heads/main/images/documentation%20green%20button.png" width="143"> |
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</a> |
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</div> |
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</div> |
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# Seed-Coder-8B-Instruct |
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<div align="left" style="line-height: 1;"> |
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<a href="https://bytedance-seed-coder.github.io/" target="_blank" style="margin: 2px;"> |
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<img alt="Homepage" src="https://img.shields.io/badge/Seed--Coder-Homepage-a468fe?color=a468fe&logoColor=white" style="display: inline-block; vertical-align: middle;"/> |
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</a> |
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<a href="https://github.com/ByteDance-Seed/Seed-Coder/blob/master/Seed-Coder.pdf" target="_blank" style="margin: 2px;"> |
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<img alt="Technical Report" src="https://img.shields.io/badge/(upcoming)-Technical%20Report-brightgreen?logo=arxiv&logoColor=white" style="display: inline-block; vertical-align: middle;"/> |
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</a> |
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<a href="https://huggingface.co/ByteDance-Seed" target="_blank" style="margin: 2px;"> |
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<img alt="Hugging Face" src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-ByteDance%20Seed-536af5?color=536af5&logoColor=white" style="display: inline-block; vertical-align: middle;"/> |
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</a> |
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<a href="https://github.com/ByteDance-Seed/Seed-Coder/blob/master/LICENSE" style="margin: 2px;"> |
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<img alt="License" src="https://img.shields.io/badge/License-MIT-f5de53?color=f5de53&logoColor=white" style="display: inline-block; vertical-align: middle;"/> |
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</a> |
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</div> |
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## Introduction |
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We are thrilled to introduce Seed-Coder, a powerful, transparent, and parameter-efficient family of open-source code models at the 8B scale, featuring base, instruct, and reasoning variants. Seed-Coder contributes to promote the evolution of open code models through the following highlights. |
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- **Model-centric:** Seed-Coder predominantly leverages LLMs instead of hand-crafted rules for code data filtering, minimizing manual effort in pretraining data construction. |
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- **Transparent:** We openly share detailed insights into our model-centric data pipeline, including methods for curating GitHub data, commits data, and code-related web data. |
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- **Powerful:** Seed-Coder achieves state-of-the-art performance among open-source models of comparable size across a diverse range of coding tasks. |
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<p align="center"> |
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<img width="100%" src="imgs/seed-coder_intro_performance.png"> |
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</p> |
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This repo contains the **Seed-Coder-8B-Instruct** model, which has the following features: |
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- Type: Causal language models |
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- Training Stage: Pretraining & Post-training |
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- Data Source: Public datasets, synthetic data |
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- Context Length: 32,768 |
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## Model Downloads |
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| Model Name | Length | Download | Notes | |
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|---------------------------------------------------------|--------|------------------------------------|-----------------------| |
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| Seed-Coder-8B-Base | 32K | 🤗 [Model](https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Base) | Pretrained on our model-centric code data. | |
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| 👉 **Seed-Coder-8B-Instruct** | 32K | 🤗 [Model](https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Instruct) | Instruction-tuned for alignment with user intent. | |
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| Seed-Coder-8B-Reasoning | 64K | 🤗 [Model](https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Reasoning) | RL trained to boost reasoning capabilities. | |
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| Seed-Coder-8B-Reasoning-bf16 | 64K | 🤗 [Model](https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Reasoning-bf16) | RL trained to boost reasoning capabilities. | |
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## Requirements |
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You will need to install the latest versions of `transformers` and `accelerate`: |
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```bash |
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pip install -U transformers accelerate |
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``` |
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## Quickstart |
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Here is a simple example demonstrating how to load the model and generate code using the Hugging Face `pipeline` API: |
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```python |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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import torch |
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model_id = "ByteDance-Seed/Seed-Coder-8B-Instruct" |
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tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True) |
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model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="auto", trust_remote_code=True) |
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messages = [ |
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{"role": "user", "content": "Write a quick sort algorithm."}, |
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] |
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input_ids = tokenizer.apply_chat_template( |
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messages, |
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tokenize=True, |
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return_tensors="pt", |
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add_generation_prompt=True, |
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).to(model.device) |
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outputs = model.generate(input_ids, max_new_tokens=512) |
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response = tokenizer.decode(outputs[0][input_ids.shape[-1]:], skip_special_tokens=True) |
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print(response) |
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``` |
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## Evaluation |
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Seed-Coder-8B-Instruct has been evaluated on a wide range of coding tasks, including code generation, code reasoning, code editing, and software engineering, achieving state-of-the-art performance among ~8B open-source models. |
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| Model | HumanEval | MBPP | MHPP | BigCodeBench (Full) | BigCodeBench (Hard) | LiveCodeBench (2410 – 2502) | |
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|:-----------------------------:|:---------:|:----:|:----:|:-------------------:|:-------------------:|:-------------------------:| |
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| CodeLlama-7B-Instruct | 40.9 | 54.0 | 6.7 | 25.7 | 4.1 | 3.6 | |
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| DeepSeek-Coder-6.7B-Instruct | 74.4 | 74.9 | 20.0 | 43.8 | 15.5 | 9.6 | |
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| CodeQwen1.5-7B-Chat | 83.5 | 77.7 | 17.6 | 43.6 | 15.5 | 3.0 | |
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| Yi-Coder-9B-Chat | 82.3 | 82.0 | 26.7 | 49.0 | 17.6 | 17.5 | |
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| Llama-3.1-8B-Instruct | 68.3 | 70.1 | 17.1 | 40.5 | 13.5 | 11.5 | |
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| OpenCoder-8B-Instruct | 83.5 | 79.1 | 30.5 | 50.9 | 18.9 | 17.1 | |
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| Qwen2.5-Coder-7B-Instruct | **88.4** | 83.5 | 26.7 | 48.8 | 20.3 | 17.3 | |
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| Qwen3-8B | 84.8 | 77.0 | 32.8 | 51.7 | 23.0 | 23.5 | |
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| Seed-Coder-8B-Instruct | 84.8 | **85.2** | **36.2** | **53.3** | **26.4** | **24.7** | |
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For detailed benchmark performance, please refer to our [📑 Technical Report](https://github.com/ByteDance-Seed/Seed-Coder/blob/master/Seed-Coder.pdf). |
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## License |
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This project is licensed under the MIT License. See the [LICENSE file](https://github.com/ByteDance-Seed/Seed-Coder/blob/master/LICENSE) for details. |
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<!-- ## Citation |
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If you find our work helpful, feel free to give us a cite. |
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``` |
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@article{zhang2025seedcoder, |
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title={Seed-Coder: Let the Code Model Curate Data for Itself}, |
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author={Xxx}, |
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year={2025}, |
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eprint={2504.xxxxx}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL}, |
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url={https://arxiv.org/abs/xxxx.xxxxx}, |
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} |
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``` --> |
