Edit model card

INT8 albert-base-v2-sst2

Post-training dynamic quantization

ONNX

This is an INT8 ONNX model quantized with Intel® Neural Compressor.

The original fp32 model comes from the fine-tuned model Alireza1044/albert-base-v2-sst2.

Test result

INT8 FP32
Accuracy (eval-accuracy) 0.9186 0.9232
Model size (MB) 59 45

Load ONNX model:

from optimum.onnxruntime import ORTModelForSequenceClassification
model = ORTModelForSequenceClassification.from_pretrained('Intel/albert-base-v2-sst2-int8-dynamic')
Downloads last month
10
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Dataset used to train Intel/albert-base-v2-sst2-int8-dynamic-inc

Collection including Intel/albert-base-v2-sst2-int8-dynamic-inc