INT8 gpt-neox-japanese-2.7b-int8
Post-training static quantization
PyTorch
This is an INT8 PyTorch model quantized with Intel® Neural Compressor.
The original fp32 model comes from the fine-tuned model abeja/gpt-neox-japanese-2.7b.
The calibration dataloader is the train dataloader. The default calibration sampling size 100 isn't divisible exactly by batch size 8, so the real sampling size is 104.
Test result
| INT8 | FP32 | |
|---|---|---|
| Accuracy (eval-loss) | 4.9920 | 3.5219 |
| Model size (MB) | 2570 | 5360 |
Load with Intel® Neural Compressor:
from optimum.intel.neural_compressor.quantization import IncQuantizedModelForCausalLM
int8_model = IncQuantizedModelForCausalLM.from_pretrained(
"Intel/gpt-neox-japanese-2.7b-int8",
)
