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Seed-Coder is a family of lightweight open-source code LLMs comprising base, instruct and reasoning models, developed by ByteDance Seed.
| Date | Stars |
|---|---|
| 2026-07-31 | 754 |
| 2026-08-02 | 754 |
| 2026-08-06 | 754 |
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# <img src="./imgs/logo.png" height="25"> Seed-Coder: Let the Code Model Curate Data for Itself
<p align="center">
🌐 <a href="https://bytedance-seed-coder.github.io/"> Homepage</a>   |   🤗 <a href="https://huggingface.co/collections/ByteDance-Seed/seed-coder-680de32c15ead6555c75b0e4">Hugging Face</a>   |   📄 <a href="https://arxiv.org/abs/2506.03524">arXiv</a>
</p>
We are thrilled to introduce **Seed-Coder** (previously known as Doubao-Coder), a family of lightweight yet powerful open-source code LLMs comprising base, instruct and reasoning models of 8B size.
Seed-Coder demonstrates that, with minimal human effort, LLMs can effectively curate code training data by themselves to drastically enhance coding capabilities.
Seed-Coder represents our initial step towards contributing to the open-source LLM ecosystem. We look forward to seeing Seed-Coder drive advances in code intelligence and empower broader applications in the open-source LLM community!
## 📢 News
[2025/05/08]🔥 We release [Seed-Coder](https://bytedance-seed-coder.github.io)!
[2025/05/14] We found an inconsistent setting of our BigCodeBench evaluation results. We already updated all the results with the aligned BigCodeBench-Completion setting.
## 🌟 Highlights
- **Model-centric:** Seed-Coder predominantly leverages LLMs instead of hand-crafted rules for code data filtering, minimizing manual effort in pretraining data construction.
- **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.
- **Powerful:** Seed-Coder achieves state-of-the-art performance among open-source models of comparable size across a diverse range of coding tasks.
## ⚡ Quick Start
We are excited to introduce **Seed-Coder**, featuring three powerful models:
| Model Name | Length | Download | Notes |
|-----------------------------|--------|------------------------------------------------------------------------------------|---------------|
| Seed-Coder-8B-Base | 32K | 🤗 [Model](https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Base) | Pretrained on our model-centric code data. |
| Seed-Coder-8B-Instruct | 32K | 🤗 [Model](https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Instruct) | Instruction-tuned for alignment with user intent. |
| Seed-Coder-8B-Reasoning | 64K | 🤗 [Model](https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Reasoning) | RL trained to boost reasoning capabilities. |
| Seed-Coder-8B-Reasoning-bf16 | 64K | 🤗 [Model](https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Reasoning-bf16) | RL trained to boost reasoning capabilities. |
All the models are publicly available on [Hugging Face collection](https://huggingface.co/collections/ByteDance-Seed/seed-coder-680de32c15ead6555c75b0e4).
### 👉🏻 Deploying Seed-Coder-8B-Instruct with `transformers`
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
model_id = "ByteDance-Seed/Seed-Coder-8B-Instruct"
tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="auto", trust_remote_code=True)
messages = [
{"role": "user", "content": "Write a quick sort algorithm."},
]
input_ids = tokenizer.apply_chat_template(
messages,
tokenize=True,
return_tensors="pt",
add_generation_prompt=True,
).to(model.device)
outputs = model.generate(input_ids, max_new_tokens=512)
response = tokenizer.decode(outputs[0][input_ids.shape[-1]:], skip_special_tokens=True)
print(response)
```
For more detailed usage instructions and model-specific configurations, please refer to the Hugging Face model pages linked above.
### 👉🏻 Deploying Seed-Coder-8B-Instruct with `vLLM`
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matched fp:273e22acbd8ed509, llm:description: 'Seed-Coder is a family of lightweight open-source code LLMs comprising base, instruct and reasoning models, developed by ByteDance Seed.'
matched fp:273e22acbd8ed509, llm:description: 'Seed-Coder is a family of lightweight open-source code LLMs comprising base, instruct and reasoning models, developed by ByteDance Seed.'
matched fp:273e22acbd8ed509, llm:description: 'Seed-Coder is a family of lightweight open-source code LLMs comprising base, instruct and reasoning models, developed by ByteDance Seed.'