---
license: apache-2.0  
base_model:  
- ByteDance-Seed/Seed-Coder-8B-Base  
---

# Seed-Coder-8B-Reasoning

## Introduction
**Seed-Coder-8B-Reasoning** is an 8-billion-parameter model further optimized for **code reasoning**, **problem-solving**, and **algorithmic thinking** tasks.  
Built upon the strong base of Seed-Coder, it undergoes additional training in sandbox environments to significantly enhance its ability to tackle complex coding problems and competitions. It features:
- Trained on a **massively curated corpus**, filtered using an **LLM-based method** to ensure high-quality real-world code, text-code alignment, and synthetic datasets.
- **Sandbox fine-tuning** to specifically strengthen **multi-step reasoning**, **algorithm design**, and **competitive programming** capabilities.
- Maintains **long-context handling** up to 32K tokens, enabling it to reason over extended problem descriptions and large input-output examples.

<p align="center">
  <img width="100%" src="imgs/large_model_comparison_split-crop.pdf">
</p>

## 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 perform code generation using the Hugging Face `pipeline` API:

```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model_id = "ByteDance-Seed/Seed-Coder-8B-Reasoning"

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=16384)
response = tokenizer.decode(outputs[0][input_ids.shape[-1]:], skip_special_tokens=True)
print(response)
```

## Evaluation

Seed-Coder-8B-Reasoning has been evaluated extensively on reasoning-intensive code benchmarks, showing:
- Significant improvements on **competitive programming** datasets and coding challenges.
- Enhanced ability to **break down complex problems**, **design correct algorithms**, and **produce efficient implementations**.
- Strong generalization to unseen problems across multiple domains (math, strings, arrays, graphs, DP, etc.).

For detailed results, please check our paper. 
<!-- For detailed results, please check our [📑 paper](https://arxiv.org/pdf/xxx.xxxxx). -->