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

Libraries

How to use hypnonyx/traffico with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("hypnonyx/traffico")
model = AutoModelForCausalLM.from_pretrained("hypnonyx/traffico", device_map="auto")
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]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use hypnonyx/traffico with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf hypnonyx/traffico:Q8_0
# Run inference directly in the terminal:
llama cli -hf hypnonyx/traffico:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf hypnonyx/traffico:Q8_0
# Run inference directly in the terminal:
llama cli -hf hypnonyx/traffico:Q8_0

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf hypnonyx/traffico:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf hypnonyx/traffico:Q8_0

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf hypnonyx/traffico:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf hypnonyx/traffico:Q8_0

Use Docker

docker model run hf.co/hypnonyx/traffico:Q8_0

LM Studio
Jan

vLLM

How to use hypnonyx/traffico with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/hypnonyx/traffico:Q8_0

SGLang

How to use hypnonyx/traffico 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 "hypnonyx/traffico" \
    --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": "hypnonyx/traffico",
		"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 "hypnonyx/traffico" \
        --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": "hypnonyx/traffico",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use hypnonyx/traffico with Ollama:
```
ollama run hf.co/hypnonyx/traffico:Q8_0
```
Unsloth Desktop
Docker Model Runner
How to use hypnonyx/traffico with Docker Model Runner:
```
docker model run hf.co/hypnonyx/traffico:Q8_0
```

Lemonade

How to use hypnonyx/traffico with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull hypnonyx/traffico:Q8_0

Run and chat with the model

lemonade run user.traffico-Q8_0

List all available models

lemonade list

Atomic Chat

hypnonyx commited on Apr 12

Commit

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@@ -24,7 +24,7 @@ model-index:
     results: []
 ---
 # Traffico - Fine-tuned on ATT&CK Data
-![Alt text](https://huggingface.co/hypnonyx/traffico/blob/main/hypnonyx_traffico.png "hypnonyx_traffico")
 ## 📋 Model Description
 Traffico is a fine-tuned language model specialized in analyzing TCP/IP network traffic and detecting cyberattacks. It maps network flow patterns to the MITRE ATT&CK framework, enabling security teams to understand adversary tactics and techniques from network behavior alone.

     results: []
 ---
 # Traffico - Fine-tuned on ATT&CK Data
+![Alt text](https://cas-bridge.xethub.hf.co/xet-bridge-us/69a7e4cc4685d39e29c58a6c/0c289b81ef240bcae3c892b79bcc32025c9bc93dcff0a9d9677ddeb62fd04602?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=cas%2F20260412%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20260412T230801Z&X-Amz-Expires=3600&X-Amz-Signature=588dad433300bbf57b055e9382784988cce240d3f218057e51f6dcdefaf63a3b&X-Amz-SignedHeaders=host&X-Xet-Cas-Uid=65738c5bc79162da909bf2ce&response-content-disposition=inline%3B+filename*%3DUTF-8%27%27hypnonyx_traffico.png%3B+filename%3D%22hypnonyx_traffico.png%22%3B&response-content-type=image%2Fpng&x-amz-checksum-mode=ENABLED&x-id=GetObject&Expires=1776038881&Policy=eyJTdGF0ZW1lbnQiOlt7IkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTc3NjAzODg4MX19LCJSZXNvdXJjZSI6Imh0dHBzOi8vY2FzLWJyaWRnZS54ZXRodWIuaGYuY28veGV0LWJyaWRnZS11cy82OWE3ZTRjYzQ2ODVkMzllMjljNThhNmMvMGMyODliODFlZjI0MGJjYWUzYzg5MmI3OWJjYzMyMDI1YzliYzkzZGNmZjBhOWQ5Njc3ZGRlYjYyZmQwNDYwMioifV19&Signature=pe%7E8m29cDZVmoi2VfpvtQsCukR2Qi-ZM%7Ec4QgwXQKSq3B5%7E-4SWG5QAGHDt-9wUTRHZqxZXRcqXUrzqgcjE52Azk5VcN8iMTlBRR4j%7E449e-dYtoNkq%7EhJDYhJN00iXjGlZYBfMlfmjzpvkLU%7EwgMYmEn-5xhgM%7E0AOzUP0BDmz6wS6OxyIEvIzwuZjtC9udbMpNpgH2LsJfNqFZKIZMjuhXusBtVgVTrmbukmbmAIX0zoChDSXEVivGcAFrSmgTU4%7EPrTwJx1f5N3eqvMMn1S5u-DD0-MPHNO6xR6DWEScHPkywJu9vXoAjJ-u%7Et-g4pZ4YHExJEFLF5M8yt3JmKQ__&Key-Pair-Id=K2L8F4GPSG1IFC "hypnonyx_traffico")
 ## 📋 Model Description
 Traffico is a fine-tuned language model specialized in analyzing TCP/IP network traffic and detecting cyberattacks. It maps network flow patterns to the MITRE ATT&CK framework, enabling security teams to understand adversary tactics and techniques from network behavior alone.