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Application: Question & Answering ML Task: MobileBERT Framework: ONNX Training information: source https://github.com/google-research/google-research/tree/master/mobilebert. Imported https://storage.googleapis.com/cloud-tpu-checkpoints/mobilebert/uncased_L-24_H-128_B-512_A-4_F-4_OPT.tar.gz checkpoint to PyTorch using Huggingface transforms. Quantaization aware training using Huggingface to save the model in ONNX model. Quality: F1 89.4% (INT8 model) Precision: INT8 Is Quantized: Yes Is ONNX: Yes Daatset: SQUAD v1.1
MobileBERT, ONNX, Squad v1.1, inference, int8 model
MobileBERT, ONNX, Squad v1.1, inference, int8 model
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 70 | |
| downloads | 18 |

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