Instructions to use exploitintel/cve-cwe-gemma4-12b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use exploitintel/cve-cwe-gemma4-12b with Transformers:

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

pipe = pipeline("text-generation", model="exploitintel/cve-cwe-gemma4-12b")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("exploitintel/cve-cwe-gemma4-12b")
model = AutoModelForImageTextToText.from_pretrained("exploitintel/cve-cwe-gemma4-12b")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.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(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use exploitintel/cve-cwe-gemma4-12b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "exploitintel/cve-cwe-gemma4-12b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "exploitintel/cve-cwe-gemma4-12b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/exploitintel/cve-cwe-gemma4-12b

SGLang

How to use exploitintel/cve-cwe-gemma4-12b 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 "exploitintel/cve-cwe-gemma4-12b" \
    --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": "exploitintel/cve-cwe-gemma4-12b",
		"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 "exploitintel/cve-cwe-gemma4-12b" \
        --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": "exploitintel/cve-cwe-gemma4-12b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use exploitintel/cve-cwe-gemma4-12b with Docker Model Runner:
```
docker model run hf.co/exploitintel/cve-cwe-gemma4-12b
```

exploitintel commited on 1 day ago

Commit

b96c46b

verified ·

1 Parent(s): 9904a9d

Upload README.md with huggingface_hub

Browse files

Files changed (1) hide show

README.md +2 -0

README.md CHANGED Viewed

@@ -21,6 +21,8 @@ tags:
 A [Gemma 4 12B](https://huggingface.co/unsloth/gemma-4-12b-it) fine-tune that maps a **CVE description** to its **CWE ID(s)**.
 - **Input:** a free-text vulnerability description (text only).
 - **Output:** the CWE ID(s) it maps to, comma-separated — e.g. `CWE-79` or `CWE-89, CWE-352`.
 - **Label space:** MITRE [CWE View-1003](https://cwe.mitre.org/data/definitions/1003.html) (~117 weakness classes). Multi-label.

 A [Gemma 4 12B](https://huggingface.co/unsloth/gemma-4-12b-it) fine-tune that maps a **CVE description** to its **CWE ID(s)**.
+> 📖 **Write-up:** [*From Essays to `CWE-319`* — how this fine-tune beats stock Gemma 4 at CWE classification](https://huggingface.co/exploitintel/cve-cwe-gemma4-12b/blob/main/blog.md)
 - **Input:** a free-text vulnerability description (text only).
 - **Output:** the CWE ID(s) it maps to, comma-separated — e.g. `CWE-79` or `CWE-89, CWE-352`.
 - **Label space:** MITRE [CWE View-1003](https://cwe.mitre.org/data/definitions/1003.html) (~117 weakness classes). Multi-label.