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Runtime error
Runtime error
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•
b47aba9
1
Parent(s):
884971a
bug fix
Browse files
app.py
CHANGED
@@ -101,16 +101,17 @@ sent_chkpt = "distilbert-base-uncased-finetuned-sst-2-english"
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sent_model_dir="sentiment_model_dir"
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#create model/token dir for sentiment classification
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create_model_dir(chkpt=sent_chkpt, model_dir=sent_model_dir)
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model_sentiment=AutoModelForSequenceClassification.from_pretrained(sent_model_dir)
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tokenizer_sentiment=AutoTokenizer.from_pretrained(sent_model_dir)
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create_onnx_model_sentiment(_model=model_sentiment, _tokenizer=tokenizer_sentiment)
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@st.cache(allow_output_mutation=True, suppress_st_warning=True, max_entries=None, ttl=None)
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def sentiment_task_selected(task,sent_model_dir=sent_model_dir):
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model_sentiment=AutoModelForSequenceClassification.from_pretrained(sent_model_dir)
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tokenizer_sentiment=AutoTokenizer.from_pretrained(sent_model_dir)
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#create inference session
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sentiment_session = ort.InferenceSession("sent_clf_onnx_dir/sentiment_classifier_onnx.onnx")
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sentiment_session_quant = ort.InferenceSession("sent_clf_onnx_dir/sentiment_classifier_onnx_quant.onnx")
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@@ -126,16 +127,17 @@ zs_chkpt = "valhalla/distilbart-mnli-12-1"
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zs_model_dir = "zs_model_dir"
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# create model/token dir for zeroshot clf
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create_model_dir(chkpt=zs_chkpt, model_dir=zs_model_dir)
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create_onnx_model_zs()
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@st.cache(allow_output_mutation=True, suppress_st_warning=True, max_entries=None, ttl=None)
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def zs_task_selected(task, zs_model_dir=zs_model_dir,onnx_dir='zeroshot_onnx_dir'):
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#model & tokenizer initialization for normal ZS classification
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model_zs=AutoModelForSequenceClassification.from_pretrained(zs_model_dir)
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tokenizer_zs=AutoTokenizer.from_pretrained(zs_model_dir)
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#create inference session from onnx model
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zs_session = ort.InferenceSession(f"{onnx_dir}/model.onnx")
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zs_session_quant = ort.InferenceSession(f"{onnx_dir}/model_quant.onnx")
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sent_model_dir="sentiment_model_dir"
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#create model/token dir for sentiment classification
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create_model_dir(chkpt=sent_chkpt, model_dir=sent_model_dir)
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@st.cache(allow_output_mutation=True, suppress_st_warning=True, max_entries=None, ttl=None)
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def sentiment_task_selected(task,sent_model_dir=sent_model_dir):
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#model & tokenizer initialization for normal sentiment classification
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model_sentiment=AutoModelForSequenceClassification.from_pretrained(sent_model_dir)
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tokenizer_sentiment=AutoTokenizer.from_pretrained(sent_model_dir)
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# create onnx model for sentiment classification
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create_onnx_model_sentiment(_model=model_sentiment, _tokenizer=tokenizer_sentiment)
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#create inference session
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sentiment_session = ort.InferenceSession("sent_clf_onnx_dir/sentiment_classifier_onnx.onnx")
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sentiment_session_quant = ort.InferenceSession("sent_clf_onnx_dir/sentiment_classifier_onnx_quant.onnx")
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zs_model_dir = "zs_model_dir"
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# create model/token dir for zeroshot clf
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create_model_dir(chkpt=zs_chkpt, model_dir=zs_model_dir)
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@st.cache(allow_output_mutation=True, suppress_st_warning=True, max_entries=None, ttl=None)
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def zs_task_selected(task, zs_model_dir=zs_model_dir,onnx_dir='zeroshot_onnx_dir'):
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#model & tokenizer initialization for normal ZS classification
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model_zs=AutoModelForSequenceClassification.from_pretrained(zs_model_dir)
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tokenizer_zs=AutoTokenizer.from_pretrained(zs_model_dir)
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# ceate onnx model for zeroshot
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create_onnx_model_zs()
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#create inference session from onnx model
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zs_session = ort.InferenceSession(f"{onnx_dir}/model.onnx")
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zs_session_quant = ort.InferenceSession(f"{onnx_dir}/model_quant.onnx")
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