BART
Collection
Adaptations on Meta's BART model
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3 items
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Updated
INT8 bart-large-mrpc
Post-training dynamic quantization
PyTorch
This is an INT8 PyTorch model quantized with huggingface/optimum-intel through the usage of Intel® Neural Compressor.
The original fp32 model comes from the fine-tuned model bart-large-mrpc.
Test result
| INT8 | FP32 | |
|---|---|---|
| Accuracy (eval-f1) | 0.9051 | 0.9120 |
| Model size (MB) | 547 | 1556.48 |
Load with optimum:
from optimum.intel import INCModelForSequenceClassification
model_id = "Intel/bart-large-mrpc-int8-dynamic"
int8_model = INCModelForSequenceClassification.from_pretrained(model_id)
ONNX
This is an INT8 ONNX model quantized with Intel® Neural Compressor.
The original fp32 model comes from the fine-tuned model bart-large-mrpc.
Test result
| INT8 | FP32 | |
|---|---|---|
| Accuracy (eval-f1) | 0.9236 | 0.9120 |
| Model size (MB) | 764 | 1555 |
Load ONNX model:
from optimum.onnxruntime import ORTModelForSequenceClassification
model = ORTModelForSequenceClassification.from_pretrained('Intel/bart-large-mrpc-int8-dynamic')
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