Instructions to use Applied-Innovation-Center/Karnak-40B-v1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Applied-Innovation-Center/Karnak-40B-v1.0 with Transformers:

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

pipe = pipeline("text-generation", model="Applied-Innovation-Center/Karnak-40B-v1.0")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Applied-Innovation-Center/Karnak-40B-v1.0")
model = AutoModelForCausalLM.from_pretrained("Applied-Innovation-Center/Karnak-40B-v1.0")
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

vLLM

How to use Applied-Innovation-Center/Karnak-40B-v1.0 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Applied-Innovation-Center/Karnak-40B-v1.0"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Applied-Innovation-Center/Karnak-40B-v1.0",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Applied-Innovation-Center/Karnak-40B-v1.0

SGLang

How to use Applied-Innovation-Center/Karnak-40B-v1.0 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 "Applied-Innovation-Center/Karnak-40B-v1.0" \
    --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": "Applied-Innovation-Center/Karnak-40B-v1.0",
		"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 "Applied-Innovation-Center/Karnak-40B-v1.0" \
        --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": "Applied-Innovation-Center/Karnak-40B-v1.0",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Applied-Innovation-Center/Karnak-40B-v1.0 with Docker Model Runner:
```
docker model run hf.co/Applied-Innovation-Center/Karnak-40B-v1.0
```

AIC-MCIT commited on Apr 23

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+Karnak
+Copyright 2026 Applied Innovation Center
+This product includes software and model weights developed by the Applied Innovation Center for the Karnak Arabic Large Language Model.
+ATTRIBUTION NOTICE:
+This model is distributed under the Apache License, Version 2.0. As per Section 4(d) of the License, any distribution of this work or derivative works must include a readable copy of this attribution notice.
+When utilizing, modifying, or building upon this model, please acknowledge the source by including the following statement in your documentation or repository:
+"Built on Karnak-Applied Innovation Center"