Instructions to use skt/A.X-4.0-Light with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use skt/A.X-4.0-Light with Transformers:

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

pipe = pipeline("text-generation", model="skt/A.X-4.0-Light")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("skt/A.X-4.0-Light")
model = AutoModelForCausalLM.from_pretrained("skt/A.X-4.0-Light")
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

vLLM

How to use skt/A.X-4.0-Light with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "skt/A.X-4.0-Light"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "skt/A.X-4.0-Light",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/skt/A.X-4.0-Light

SGLang

How to use skt/A.X-4.0-Light 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 "skt/A.X-4.0-Light" \
    --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": "skt/A.X-4.0-Light",
		"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 "skt/A.X-4.0-Light" \
        --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": "skt/A.X-4.0-Light",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use skt/A.X-4.0-Light with Docker Model Runner:
```
docker model run hf.co/skt/A.X-4.0-Light
```

Update tokenizer_config.json

by cateto - opened Jul 9, 2025

base: refs/heads/main

←

from: refs/pr/2

Discussion Files changed

-1

cateto

Jul 9, 2025

for this error
A decoder-only architecture is being used, but right-padding was detected! For correct generation results, please set `padding_side='left'` when initializing the tokenizer.

Update tokenizer_config.json4e3a9e0f

singleheart

SK Telecom org Jul 9, 2025

Thank you for your valuable suggestion. After careful review, we have decided that it is not necessary to specify the side, so we have removed it. Please use the latest version.

singleheart changed pull request status to closed Jul 9, 2025

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