nyu-mll/glue
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How to use Intel/albert-base-v2-MRPC-int8-inc with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="Intel/albert-base-v2-MRPC-int8-inc") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Intel/albert-base-v2-MRPC-int8-inc")
model = AutoModelForSequenceClassification.from_pretrained("Intel/albert-base-v2-MRPC-int8-inc")Model Description: This model is a Albert fine-tuned on MPRC dynamically quantized with optimum-intel through the usage of huggingface/optimum-intel through the usage of Intel® Neural Compressor.
To load the quantized model, you can do as follows:
from optimum.intel import INCModelForSequenceClassification
model = INCModelForSequenceClassification.from_pretrained("Intel/albert-base-v2-MRPC-int8")
| INT8 | FP32 | |
|---|---|---|
| Accuracy (eval-f1) | 0.9193 | 0.9263 |
| Model size (MB) | 45.0 | 46.7 |