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82d2ad2
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Parent(s):
e867e2e
Update app.py
Browse files
app.py
CHANGED
@@ -32,7 +32,7 @@ m = torch.load('model.pt', map_location=torch.device('cpu'))
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model.load_state_dict(m)
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model.to(device);
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-
str = st.text_input( 'Enter 1-4 words of the beginning of the text, and wait a minute' , '
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# model without additional training
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# prompt is a string that will be accepted as input and continued by the model
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@@ -59,7 +59,7 @@ out1 = model_init.generate(
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# how much (try) not to repeat n_gram in a row
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no_repeat_ngram_size=3,
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# how many generations to return
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num_return_sequences=
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).cpu().numpy() #).numpy()
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st.write('\n------------------\n')
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@@ -88,12 +88,4 @@ with torch.inference_mode():
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top_p=0.6,
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no_repeat_ngram_size=2,
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num_return_sequences=3,
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).cpu().numpy() #).cpu().numpy()
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-
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st.subheader( 'Texts on a model trained with documents of all subjects and retrained with jokes:' )
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n = 0
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for out_ in out2:
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n += 1
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st.write(tokenizer.decode(out_).rpartition('.')[0],'.')
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# print(textwrap.fill(tokenizer.decode(out_), 100), end='\n------------------\n')
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st.write('\n------------------\n')
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model.load_state_dict(m)
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model.to(device);
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+
str = st.text_input( 'Enter 1-4 words of the beginning of the text, and wait a minute' , '' )
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# model without additional training
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# prompt is a string that will be accepted as input and continued by the model
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# how much (try) not to repeat n_gram in a row
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no_repeat_ngram_size=3,
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# how many generations to return
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num_return_sequences=1,
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).cpu().numpy() #).numpy()
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st.write('\n------------------\n')
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top_p=0.6,
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no_repeat_ngram_size=2,
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num_return_sequences=3,
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).cpu().numpy() #).cpu().numpy()
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