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056a08f
1
Parent(s):
37e3aef
Update app.py
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app.py
CHANGED
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@@ -14,30 +14,29 @@ topics=["NFT", "Blockchain", "Metaverse"]
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choice = st.sidebar.selectbox("Select one topic", topics)
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if choice == 'NFT':
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keywords=st.text_area("Input 4 keywords here: (optional)")
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length=st.text_area("How long should be your text? (default: 512 words)")
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if st.button("Generate"):
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prompt = "<|startoftext|>"
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generated = torch.tensor(tokenizer.encode(prompt)).unsqueeze(0)
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generated = generated.to(device)
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sample_outputs = model.generate(
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generated,
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do_sample=True,
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top_k=50,
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max_length = 512,
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top_p=0.95,
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num_return_sequences=1
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)
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for i, sample_output in enumerate(sample_outputs):
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generated_text = tokenizer.decode(sample_output,
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skip_special_tokens=True)
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#st.text("Keywords: {}\n".format(keywords))
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#st.text("Length in number of words: {}\n".format(length))
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st.text("This is your tailored blog article {generated_text}")
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summary = summarize(generated_text, num_sentences=1)
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st.text("This is a tweet-sized summary of your article {summary}")
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else:
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st.write("Topic not available yet")
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choice = st.sidebar.selectbox("Select one topic", topics)
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if choice == 'NFT':
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keywords=st.text_area("Input 4 keywords here: (optional)")
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length=st.text_area("How long should be your text? (default: 512 words)")
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if st.button("Generate"):
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prompt = "<|startoftext|>"
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generated = torch.tensor(tokenizer.encode(prompt)).unsqueeze(0)
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generated = generated.to(device)
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sample_outputs = model.generate(
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generated,
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do_sample=True,
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top_k=50,
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max_length = 512,
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top_p=0.95,
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num_return_sequences=1
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)
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for i, sample_output in enumerate(sample_outputs):
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generated_text = tokenizer.decode(sample_output, skip_special_tokens=True)
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#st.text("Keywords: {}\n".format(keywords))
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#st.text("Length in number of words: {}\n".format(length))
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st.text("This is your tailored blog article {generated_text}")
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summary = summarize(generated_text, num_sentences=1)
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st.text("This is a tweet-sized summary of your article {summary}")
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else:
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st.write("Topic not available yet")
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