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grpathak22
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Update app.py
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app.py
CHANGED
@@ -1,22 +1,22 @@
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import modelrun.py
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from transformers import AutoTokenizer, MT5ForConditionalGeneration
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from transformers import T5Tokenizer
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import streamlit as st
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import pandas as pd
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from datasets import Dataset
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import torch
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from datasets import Dataset, DatasetDict
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from transformers import Trainer, TrainingArguments
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prompt = st.text_input("Enter your proverb: ")
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# Tokenize the input prompt
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input_ids = tokenizer.encode(prompt, return_tensors='pt')
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# Generate the output
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output_ids = model.generate(input_ids, max_length=256)
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# Decode the output to text
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output_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
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st.write(output_text)
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import modelrun.py
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# from transformers import AutoTokenizer, MT5ForConditionalGeneration
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# from transformers import T5Tokenizer
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# import streamlit as st
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# import pandas as pd
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# from datasets import Dataset
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# import torch
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# from datasets import Dataset, DatasetDict
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# from transformers import Trainer, TrainingArguments
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# prompt = st.text_input("Enter your proverb: ")
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# # Tokenize the input prompt
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# input_ids = tokenizer.encode(prompt, return_tensors='pt')
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# # Generate the output
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# output_ids = model.generate(input_ids, max_length=256)
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# # Decode the output to text
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# output_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
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# st.write(output_text)
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