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 May 7, 2025

Commit

5d7fdbf

verified ·

1 Parent(s): d686f61

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@@ -19,11 +19,11 @@ Seed-Coder-8B-Base serves as the foundation for Seed-Coder-8B-Instruct and Seed-
 </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
@@ -100,7 +100,7 @@ It demonstrates strong capabilities in:
 | MultiPL-E  |           44.7           |        61.0       |       58.8       |        67.6        |
 | CruxEval-O |           41.0           |        43.9       |       56.0       |        48.4        |
-For detailed benchmark results, please refer to our [📑 paper](https://github.com/ByteDance-Seed/Seed-Coder/blob/master/Seed-Coder.pdf).
 <!-- ## Citation

 </p>
 ## Model Downloads
+| Model Name                  | Type     | Length | Download   |    Notes |
+|---------------------------------------------------------|----------|--------|------------------------------------|-----------------------|
+| 👉 **Seed-Coder-8B-Base**           | base     | 32K    | 🤗 [Model](https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Base)   |  Pretrained on our model-centric code data.  |
+| Seed-Coder-8B-Instruct             | instruct  | 32K    | 🤗 [Model](https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Instruct)   |  SFT trained to better follow user prompts.  |
+| Seed-Coder-8B-Reasoning            | reasoning | 32K    | 🤗 [Model](https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Reasoning)   |  RL trained to boost complex reasoning capabilities.  |
 ## Requirements
 | MultiPL-E  |           44.7           |        61.0       |       58.8       |        67.6        |
 | CruxEval-O |           41.0           |        43.9       |       56.0       |        48.4        |
+For detailed benchmark performance, please refer to our [📑 technical report](https://github.com/ByteDance-Seed/Seed-Coder/blob/master/Seed-Coder.pdf).
 <!-- ## Citation