Instructions to use fdtn-ai/Foundation-Sec-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use fdtn-ai/Foundation-Sec-8B with Transformers:

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

pipe = pipeline("text-generation", model="fdtn-ai/Foundation-Sec-8B")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("fdtn-ai/Foundation-Sec-8B")
model = AutoModelForCausalLM.from_pretrained("fdtn-ai/Foundation-Sec-8B", device_map="auto")

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use fdtn-ai/Foundation-Sec-8B with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/fdtn-ai/Foundation-Sec-8B

SGLang

How to use fdtn-ai/Foundation-Sec-8B 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 "fdtn-ai/Foundation-Sec-8B" \
    --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": "fdtn-ai/Foundation-Sec-8B",
		"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 "fdtn-ai/Foundation-Sec-8B" \
        --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": "fdtn-ai/Foundation-Sec-8B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use fdtn-ai/Foundation-Sec-8B with Docker Model Runner:
```
docker model run hf.co/fdtn-ai/Foundation-Sec-8B
```

takahiroma

robustdev commited on Aug 26, 2025

Commit

9e6bb1f

verified ·

1 Parent(s): 30addf8

Add cookbook link to README (#15)

Browse files

- Add cookbook link to README (45e31e2a67359431bbfd73b6e312d9a3941a8e89)

Co-authored-by: Robust Dev <robustdev@users.noreply.huggingface.co>

Files changed (1) hide show

README.md +1 -0

README.md CHANGED Viewed

@@ -89,6 +89,7 @@ The following uses are out-of-scope and are neither recommended nor intended use
 ## How to Get Started with the Model
 Use the code below to get started with the model.
 ```python
 # Import the required libraries

 ## How to Get Started with the Model
 Use the code below to get started with the model.
+[The cookbook](https://github.com/cisco-foundation-ai/cookbook) provides example use cases, code samples for adoption, and references.
 ```python
 # Import the required libraries