SKT AI LABS

SKT-ST-X-0-3B-V1

🛠️ Quick Start Guide

Installation

pip install transformers accelerate torch peft bitsandbytes

Basic Inference

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_id = "sKT-Ai-Labs/SKT-ST-X-0-3B"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    device_map="auto",
    torch_dtype=torch.float16
)

prompt = "What is Quantum Physics?"
formatted = f"<|user|>\n{prompt}\n<|assistant|>\n"
inputs = tokenizer(formatted, return_tensors="pt").to("cuda")

outputs = model.generate(**inputs, max_new_tokens=100)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response.split("<|assistant|>")[-1].strip())

⚡ 4-bit Quantization (Low VRAM)

from transformers import BitsAndBytesConfig

quant_config = BitsAndBytesConfig(
    load_in_4bit=True,
    bnb_4bit_compute_dtype=torch.float16)

model = AutoModelForCausalLM.from_pretrained(
    model_id,
    quantization_config=quant_config,
    device_map="auto"
)

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📜 License & Citation

This model is released under the Apache-2.0 License.

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• Third Party Notices

@misc{SKT-ST-X-0-3B,
  author = {SKT AI LABS, India},
  title = {SKT-ST-X-0-3B: A Compact Mixture of Experts Model},
  year = {2026},
  publisher = {Hugging Face},
  url = {https://huggingface.co/sKT-Ai-Labs/SKT-ST-X-0-3B}
}