Instructions to use ByteDance-Seed/Seed-Coder-8B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ByteDance-Seed/Seed-Coder-8B-Base with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="ByteDance-Seed/Seed-Coder-8B-Base")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ByteDance-Seed/Seed-Coder-8B-Base")
model = AutoModelForCausalLM.from_pretrained("ByteDance-Seed/Seed-Coder-8B-Base")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use ByteDance-Seed/Seed-Coder-8B-Base with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ByteDance-Seed/Seed-Coder-8B-Base"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ByteDance-Seed/Seed-Coder-8B-Base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ByteDance-Seed/Seed-Coder-8B-Base

SGLang

How to use ByteDance-Seed/Seed-Coder-8B-Base with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "ByteDance-Seed/Seed-Coder-8B-Base" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ByteDance-Seed/Seed-Coder-8B-Base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "ByteDance-Seed/Seed-Coder-8B-Base" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ByteDance-Seed/Seed-Coder-8B-Base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ByteDance-Seed/Seed-Coder-8B-Base with Docker Model Runner:
```
docker model run hf.co/ByteDance-Seed/Seed-Coder-8B-Base
```

yuyuzhang commited on Jun 6, 2025

Commit

8094181

verified ·

1 Parent(s): f325b24

Update README.md

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Files changed (1) hide show

README.md +12 -12

README.md CHANGED Viewed

@@ -11,8 +11,8 @@ pipeline_tag: text-generation
     <img alt="Homepage" src="https://img.shields.io/badge/Seed--Coder-Homepage-a468fe?color=a468fe&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
   </a>
-  <a href="https://github.com/ByteDance-Seed/Seed-Coder/blob/master/Seed-Coder.pdf" target="_blank" style="margin: 2px;">
-    <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;"/>
   </a>
   <a href="https://huggingface.co/ByteDance-Seed" target="_blank" style="margin: 2px;">
@@ -130,18 +130,18 @@ For detailed benchmark performance, please refer to our [📑 Technical Report](
 This project is licensed under the MIT License. See the [LICENSE file](https://github.com/ByteDance-Seed/Seed-Coder/blob/master/LICENSE) for details.
-<!-- ## Citation
 If you find Seed-Coder helpful, please consider citing our work:
 ```
-@article{bytedance2025seedcoder,
-    title={Seed-Coder: Let the Code Model Curate Data for Itself},
-    author={Xxx},
-    year={2025},
-    eprint={xxxx.xxxxx},
-    archivePrefix={arXiv},
-    primaryClass={cs.AI},
-    url={https://arxiv.org/abs/xxxx.xxxxx},
 }
-```  -->

     <img alt="Homepage" src="https://img.shields.io/badge/Seed--Coder-Homepage-a468fe?color=a468fe&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
   </a>
+  <a href="https://arxiv.org/abs/2506.03524" target="_blank" style="margin: 2px;">
+    <img alt="Technical Report" src="https://img.shields.io/badge/-Technical%20Report-brightgreen?logo=arxiv&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
   </a>
   <a href="https://huggingface.co/ByteDance-Seed" target="_blank" style="margin: 2px;">
 This project is licensed under the MIT License. See the [LICENSE file](https://github.com/ByteDance-Seed/Seed-Coder/blob/master/LICENSE) for details.
+## Citation
 If you find Seed-Coder helpful, please consider citing our work:
 ```
+@misc{seed2025seedcoderletcodemodel,
+      title={{Seed-Coder}: Let the Code Model Curate Data for Itself},
+      author={{ByteDance Seed} and Yuyu Zhang and Jing Su and Yifan Sun and Chenguang Xi and Xia Xiao and Shen Zheng and Anxiang Zhang and Kaibo Liu and Daoguang Zan and Tao Sun and Jinhua Zhu and Shulin Xin and Dong Huang and Yetao Bai and Lixin Dong and Chao Li and Jianchong Chen and Hanzhi Zhou and Yifan Huang and Guanghan Ning and Xierui Song and Jiaze Chen and Siyao Liu and Kai Shen and Liang Xiang and Yonghui Wu},
+      year={2025},
+      eprint={2506.03524},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2506.03524},
 }
+```