Instructions to use GilGamez-com/Leviathan-v4.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use GilGamez-com/Leviathan-v4.2 with Transformers:

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

pipe = pipeline("text-generation", model="GilGamez-com/Leviathan-v4.2")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("GilGamez-com/Leviathan-v4.2", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use GilGamez-com/Leviathan-v4.2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "GilGamez-com/Leviathan-v4.2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "GilGamez-com/Leviathan-v4.2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/GilGamez-com/Leviathan-v4.2

SGLang

How to use GilGamez-com/Leviathan-v4.2 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 "GilGamez-com/Leviathan-v4.2" \
    --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": "GilGamez-com/Leviathan-v4.2",
		"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 "GilGamez-com/Leviathan-v4.2" \
        --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": "GilGamez-com/Leviathan-v4.2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use GilGamez-com/Leviathan-v4.2 with Docker Model Runner:
```
docker model run hf.co/GilGamez-com/Leviathan-v4.2
```

Leviathan-v4.2 / Modelfile

Archalean

feat: add Ollama Modelfile

c685090 verified 6 days ago

Raw History Blame Contribute Delete

660 Bytes

FROM ./Leviathan-v4.2.Q4_K_M.gguf

TEMPLATE """{{ if .System }}<|im_start|>system
{{ .System }}<|im_end|>
{{ end }}{{ if .Prompt }}<|im_start|>user
{{ .Prompt }}<|im_end|>
{{ end }}<|im_start|>assistant
<think>
"""

SYSTEM """You are Leviathan v4.2, an autonomous AI assistant and enterprise orchestrator created by GilGamez. You specialize in full-stack software engineering, Purple Team cybersecurity defense, and native operations across the GilGamez platform ecosystem."""

PARAMETER stop "<|im_start|>"
PARAMETER stop "<|im_end|>"
PARAMETER stop "</think>"
PARAMETER temperature 0.6
PARAMETER top_p 0.9
PARAMETER repeat_penalty 1.1
PARAMETER num_ctx 8192

	FROM ./Leviathan-v4.2.Q4_K_M.gguf

	TEMPLATE """{{ if .System }}<\|im_start\|>system
	{{ .System }}<\|im_end\|>
	{{ end }}{{ if .Prompt }}<\|im_start\|>user
	{{ .Prompt }}<\|im_end\|>
	{{ end }}<\|im_start\|>assistant
	<think>
	"""

	SYSTEM """You are Leviathan v4.2, an autonomous AI assistant and enterprise orchestrator created by GilGamez. You specialize in full-stack software engineering, Purple Team cybersecurity defense, and native operations across the GilGamez platform ecosystem."""

	PARAMETER stop "<\|im_start\|>"
	PARAMETER stop "<\|im_end\|>"
	PARAMETER stop "</think>"
	PARAMETER temperature 0.6
	PARAMETER top_p 0.9
	PARAMETER repeat_penalty 1.1
	PARAMETER num_ctx 8192