upload int8 onnx model
Browse filesSigned-off-by: yuwenzho <[email protected]>
- README.md +37 -0
- config.json +37 -0
- model.onnx +3 -0
- tokenizer.json +0 -0
README.md
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---
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license: mit
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---
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---
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language: en
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license: mit
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tags:
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- text-classfication
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- int8
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- Intel® Neural Compressor
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- PostTrainingDynamic
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- onnx
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datasets:
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- mrpc
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metrics:
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- f1
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---
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# INT8 roberta base finetuned MRPC
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## Post-training dynamic quantization
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### ONNX
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This is an INT8 ONNX model quantized with [Intel® Neural Compressor](https://github.com/intel/neural-compressor).
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The original fp32 model comes from the fine-tuned model [Intel/roberta-base-mrpc](https://huggingface.co/Intel/roberta-base-mrpc).
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#### Test result
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| |INT8|FP32|
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|---|:---:|:---:|
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| **Accuracy (eval-f1)** |0.9085|0.9138|
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| **Model size (MB)** |122|476|
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#### Load ONNX model:
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```python
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from optimum.onnxruntime import ORTModelForSequenceClassification
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model = ORTModelForSequenceClassification.from_pretrained('Intel/roberta-base-mrpc-int8-dynamic')
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```
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config.json
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{
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"_name_or_path": "roberta-base",
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"architectures": [
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"RobertaForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"classifier_dropout": null,
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"eos_token_id": 2,
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"finetuning_task": "mrpc",
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "not_equivalent",
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"1": "equivalent"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"equivalent": 1,
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"not_equivalent": 0
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},
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"model_type": "roberta",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.18.0",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 50265
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}
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model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:4385f8989ef927321b1688a9994c5cb50b72ed4fe25ac256ea1be9ff497755ce
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size 127041708
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tokenizer.json
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