Added hf_token
Browse files
app.py
CHANGED
@@ -5,8 +5,11 @@ import altair as alt
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from transformers import pipeline
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from transformers import AutoTokenizer
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import warnings
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warnings.filterwarnings('ignore')
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# set up altair theme
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font = 'NotoSansSinhala.ttf'
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font_color = '#858991'
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@@ -36,7 +39,7 @@ def get_model_id():
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model_list = ["Ransaka/sinhala-bert-small","Ransaka/SinhalaRoberta","keshan/SinhalaBERTo"]
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selected_model = st.selectbox("Select Model", model_list)
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st.write(f"Selected model: {selected_model}")
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tokenizer = AutoTokenizer.from_pretrained(selected_model)
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mask_token = tokenizer.mask_token
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return selected_model,mask_token
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@@ -95,7 +98,7 @@ if __name__ == "__main__":
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if sentence:
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prompt = get_prompt(mask_token)
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if prompt and st.button("Classify"):
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pipe = pipeline("fill-mask", model=model_id)
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output = pipe(sentence + prompt, targets=TARGETS, top_k =len(TARGETS))
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output = pd.DataFrame(output)
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output['score'] = output['score'].apply(lambda x:x/sum(output['score']))
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from transformers import pipeline
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from transformers import AutoTokenizer
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import warnings
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import os
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warnings.filterwarnings('ignore')
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hf_token = os.environ['HF_READ']
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# set up altair theme
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font = 'NotoSansSinhala.ttf'
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font_color = '#858991'
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model_list = ["Ransaka/sinhala-bert-small","Ransaka/SinhalaRoberta","keshan/SinhalaBERTo"]
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selected_model = st.selectbox("Select Model", model_list)
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st.write(f"Selected model: {selected_model}")
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tokenizer = AutoTokenizer.from_pretrained(selected_model, token=hf_token)
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mask_token = tokenizer.mask_token
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return selected_model,mask_token
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if sentence:
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prompt = get_prompt(mask_token)
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if prompt and st.button("Classify"):
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pipe = pipeline("fill-mask", model=model_id, token=hf_token)
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output = pipe(sentence + prompt, targets=TARGETS, top_k =len(TARGETS))
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output = pd.DataFrame(output)
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output['score'] = output['score'].apply(lambda x:x/sum(output['score']))
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