Instructions to use clouditera/secgpt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use clouditera/secgpt with Transformers:

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

pipe = pipeline("text-generation", model="clouditera/secgpt")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("clouditera/secgpt")
model = AutoModelForCausalLM.from_pretrained("clouditera/secgpt")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use clouditera/secgpt with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "clouditera/secgpt"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "clouditera/secgpt",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/clouditera/secgpt

SGLang

How to use clouditera/secgpt 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 "clouditera/secgpt" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "clouditera/secgpt",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "clouditera/secgpt" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "clouditera/secgpt",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use clouditera/secgpt with Docker Model Runner:
```
docker model run hf.co/clouditera/secgpt
```

wygbb commited on Apr 14, 2025

Commit

b742806

verified ·

1 Parent(s): afaf935

Update README.md

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@@ -1,3 +1,15 @@
 # 🌐 SecGPT：全球首个网络安全开源大模型
 ## 🔍 模型简介
@@ -32,11 +44,6 @@ SecGPT 融合了自然语言理解、代码生成、安全知识推理等核心
   -  https://github.com/Clouditera/secgpt
-- **模型下载地址：**
-  - HuggingFace:  https://huggingface.co/clouditera/secgpt
-  - ModelScope: [即将上线]
 - **数据集下载地址：**
   - https://huggingface.co/datasets/clouditera/security-paper-datasets
@@ -329,7 +336,4 @@ SecGPT 是一个面向网络安全领域的大模型开源项目，我们相信
 - 本项目为研究与交流目的所构建，输出内容可能受限于模型训练数据的覆盖范围；
 - 用户在使用模型过程中，应自行判断其输出的正确性与适用性；
 - 若您计划将本模型用于 **公开发布或商业化部署**，请务必明确承担相关法律和合规责任；
-- 本项目的开发者对因使用本模型（包括但不限于模型本身、训练数据、输出内容）所可能产生的任何直接或间接损害概不负责。

+---
+license: apache-2.0
+language:
+- zh
+- en
+base_model:
+- Qwen/Qwen2.5-14B-Instruct
+tags:
+- cybersecurity
+- security
+- network-security
+---
 # 🌐 SecGPT：全球首个网络安全开源大模型
 ## 🔍 模型简介
   -  https://github.com/Clouditera/secgpt
 - **数据集下载地址：**
   - https://huggingface.co/datasets/clouditera/security-paper-datasets
 - 本项目为研究与交流目的所构建，输出内容可能受限于模型训练数据的覆盖范围；
 - 用户在使用模型过程中，应自行判断其输出的正确性与适用性；
 - 若您计划将本模型用于 **公开发布或商业化部署**，请务必明确承担相关法律和合规责任；
+- 本项目的开发者对因使用本模型（包括但不限于模型本身、训练数据、输出内容）所可能产生的任何直接或间接损害概不负责。