coco101010/Qwen3-32B-GPTQ-4bit-default-calibration

This model is created with the following code:

from datasets import load_dataset
from gptqmodel import GPTQModel, QuantizeConfig
from huggingface_hub import constants

model_id = "Qwen/Qwen3-32B"
# Save the quantized model in the HF cache directory
cache_dir = constants.HF_HUB_CACHE
quant_path = os.path.join(cache_dir, "models--quantized--" + model_id.replace("/", "--"))
os.makedirs(quant_path, exist_ok=True)

# Load calibration data (1024 samples from C4)
calibration_dataset = load_dataset(
    "allenai/c4",
    data_files="en/c4-train.00001-of-01024.json.gz",
    split="train"
  ).select(range(1024))["text"]

# Configure and run quantization
quant_config = QuantizeConfig(bits=4, group_size=128)
model = GPTQModel.load(model_id, quant_config)
model.quantize(calibration_dataset, batch_size=2)
model.save(quant_path)