Instructions to use CubicLabs/AXL-Secure-Lion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use CubicLabs/AXL-Secure-Lion with Transformers:

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

pipe = pipeline("text-generation", model="CubicLabs/AXL-Secure-Lion")

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("CubicLabs/AXL-Secure-Lion", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use CubicLabs/AXL-Secure-Lion 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 CubicLabs/AXL-Secure-Lion:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf CubicLabs/AXL-Secure-Lion:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf CubicLabs/AXL-Secure-Lion:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf CubicLabs/AXL-Secure-Lion:Q4_K_M

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 CubicLabs/AXL-Secure-Lion:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf CubicLabs/AXL-Secure-Lion:Q4_K_M

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 CubicLabs/AXL-Secure-Lion:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf CubicLabs/AXL-Secure-Lion:Q4_K_M

Use Docker

docker model run hf.co/CubicLabs/AXL-Secure-Lion:Q4_K_M

LM Studio
Jan

vLLM

How to use CubicLabs/AXL-Secure-Lion with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/CubicLabs/AXL-Secure-Lion:Q4_K_M

SGLang

How to use CubicLabs/AXL-Secure-Lion 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 "CubicLabs/AXL-Secure-Lion" \
    --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": "CubicLabs/AXL-Secure-Lion",
		"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 "CubicLabs/AXL-Secure-Lion" \
        --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": "CubicLabs/AXL-Secure-Lion",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Ollama
How to use CubicLabs/AXL-Secure-Lion with Ollama:
```
ollama run hf.co/CubicLabs/AXL-Secure-Lion:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use CubicLabs/AXL-Secure-Lion with Docker Model Runner:
```
docker model run hf.co/CubicLabs/AXL-Secure-Lion:Q4_K_M
```

Lemonade

How to use CubicLabs/AXL-Secure-Lion with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull CubicLabs/AXL-Secure-Lion:Q4_K_M

Run and chat with the model

lemonade run user.AXL-Secure-Lion-Q4_K_M

List all available models

lemonade list

Atomic Chat

AXL-Secure-Lion

File size: 291 Bytes

350ea7d

{
  "model": "AXL-Secure-Lion",
  "params": 11700640,
  "steps": 172,
  "time": 601.8940315246582,
  "final_loss": 0.2243965119123459,
  "perplexity": 1.23,
  "gguf_mb": 22.4,
  "optimizer": "Lion",
  "attention": "SDPA",
  "max_seq_len": 2048,
  "data": "axl_secure_pairs.txt"
}