pass on tokenizer to pipeline (#4489)
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@@ -103,7 +103,7 @@ def load_graph_from_args(framework: str, model: str, tokenizer: Optional[str] =
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print("Loading pipeline (model: {}, tokenizer: {})".format(model, tokenizer))
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# Allocate tokenizer and model
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return pipeline("feature-extraction", model=model, framework=framework)
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return pipeline("feature-extraction", model=model, tokenizer=tokenizer, framework=framework)
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def convert_pytorch(nlp: Pipeline, opset: int, output: str, use_external_format: bool):
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