Instructions to use FrostWolfAI/Frost-Cyber-Mini-1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use FrostWolfAI/Frost-Cyber-Mini-1.0 with Transformers:

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

pipe = pipeline("text-generation", model="FrostWolfAI/Frost-Cyber-Mini-1.0")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("FrostWolfAI/Frost-Cyber-Mini-1.0")
model = AutoModelForCausalLM.from_pretrained("FrostWolfAI/Frost-Cyber-Mini-1.0", 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=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use FrostWolfAI/Frost-Cyber-Mini-1.0 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "FrostWolfAI/Frost-Cyber-Mini-1.0"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FrostWolfAI/Frost-Cyber-Mini-1.0",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/FrostWolfAI/Frost-Cyber-Mini-1.0

SGLang

How to use FrostWolfAI/Frost-Cyber-Mini-1.0 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 "FrostWolfAI/Frost-Cyber-Mini-1.0" \
    --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": "FrostWolfAI/Frost-Cyber-Mini-1.0",
		"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 "FrostWolfAI/Frost-Cyber-Mini-1.0" \
        --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": "FrostWolfAI/Frost-Cyber-Mini-1.0",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use FrostWolfAI/Frost-Cyber-Mini-1.0 with Docker Model Runner:
```
docker model run hf.co/FrostWolfAI/Frost-Cyber-Mini-1.0
```

Access Frost Cyber Mini 1.0

This repository is publicly accessible, but you have to accept the conditions to access its files and content.

Frost Cyber Mini 1.0 is an uncensored (abliterated) offensive-security model. Its safety filtering is substantially reduced and it will produce exploit code, payloads, and attacker tradecraft on request. Access is granted for AUTHORIZED security testing, defensive research, and education only. By requesting access you agree to the terms below.

Gated model

You can list files but not access them

Preview of files found in this repository

Access Frost Cyber Mini 1.0

Gated model You can list files but not access them

Gated model

You can list files but not access them