'mint autosave'
Browse files- Dockerfile +1 -1
- app.py +2 -3
Dockerfile
CHANGED
@@ -1,4 +1,4 @@
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-
FROM
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WORKDIR /app
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FROM python:3.8.9
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WORKDIR /app
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app.py
CHANGED
@@ -12,12 +12,11 @@ def analyze(input, model):
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#text insert
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input = st.text_area("insert text to be analyzed", value="Nice to see you today.", height=None, max_chars=None, key=None, help=None, on_change=None, args=None, kwargs=None, placeholder=None, disabled=False, label_visibility="visible")
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model_name = st.text_input("choose a transformer model", value="")
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if model_name:
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model = TFAutoModelForSequenceClassification.from_pretrained(model_name)
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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classifier = pipeline('sentiment-analysis', model=model, tokenizer=tokenizer)
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-
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else:
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classifier = pipeline('sentiment-analysis')
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@@ -25,5 +24,5 @@ else:
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if st.button('Analyze'):
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st.write(classifier(input))
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else:
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-
st.write('
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#text insert
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input = st.text_area("insert text to be analyzed", value="Nice to see you today.", height=None, max_chars=None, key=None, help=None, on_change=None, args=None, kwargs=None, placeholder=None, disabled=False, label_visibility="visible")
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+
model_name = st.text_input("choose a transformer model (nothing for default)", value="")
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if model_name:
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model = TFAutoModelForSequenceClassification.from_pretrained(model_name)
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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classifier = pipeline('sentiment-analysis', model=model, tokenizer=tokenizer)
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else:
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classifier = pipeline('sentiment-analysis')
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if st.button('Analyze'):
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st.write(classifier(input))
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else:
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+
st.write('Excited to analyze!')
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