Upload model, config, and model card
Browse files- 1/model.pt +3 -0
- README.md +19 -0
- config.pbtxt +61 -0
1/model.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:7eafd4c3b57ec8980f22603fa255774f4cf214ca91c7ef1ce544157326e82c68
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size 1330968444
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README.md
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---
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language:
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- en
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thumbnail:
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tags:
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- question-answering
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- torchscript
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- FastNN
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license: mit
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datasets:
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- squad
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metrics:
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---
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# TorchScript model of bert-large-cased-whole-word-masking-finetuned-squad
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## Model description
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A serialized torchscript model of bert-large-cased-whole-word-masking-finetuned-squad with a config.pbtxt for deployment using NVIDIA Triton Inference Server.
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config.pbtxt
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name: "bert-large-cased-whole-word-masking-finetuned-squad"
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platform: "pytorch_libtorch"
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max_batch_size: 64
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input [
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{
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name: "input__0"
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data_type: TYPE_INT64
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dims: [512]
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},
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{
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name: "input__1"
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data_type: TYPE_INT64
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dims: [512]
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},
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{
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name: "input__2"
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data_type: TYPE_INT64
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dims: [512]
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},
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{
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name: "input__3"
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data_type: TYPE_INT64
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dims: [1]
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},
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{
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name: "input__4"
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data_type: TYPE_INT64
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dims: [1]
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},
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{
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name: "input__5"
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data_type: TYPE_FP32
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dims: [512]
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}
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]
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output [
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{
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name: "output__0"
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data_type: TYPE_FP32
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dims: [512]
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},
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{
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name: "output__1"
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data_type: TYPE_FP32
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dims: [512]
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},
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{
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name: "output__2"
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data_type: TYPE_INT64
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dims: [1]
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}
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]
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dynamic_batching {
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preferred_batch_size: [ 1,2,4,8,16,32,64 ]
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max_queue_delay_microseconds: 30000
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}
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version_policy: { latest { num_versions : 1 }}
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optimization {
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graph { level: 1 }
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}
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