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Add new model - bloom 560
Browse filesThe 350 model has changed to the 560 model (count including embedding weights).
app.py
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@@ -2,7 +2,7 @@ import transformers
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from transformers import pipeline
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import gradio as gr
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checkpoint_choices = ['wvangils/GPT-Medium-Beatles-Lyrics-finetuned-newlyrics', 'wvangils/GPT-Neo-125m-Beatles-Lyrics-finetuned-newlyrics', 'wvangils/BLOOM-
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# Create function for generation
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def generate_beatles(checkpoint, input_prompt, temperature, top_p):
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@@ -33,7 +33,7 @@ output_box = gr.Textbox(label="Lyrics by The Beatles and chosen language model:"
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title='Beatles lyrics generator'
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description="<p style='text-align: center'>Multiple language models were fine-tuned on lyrics from The Beatles to generate Beatles-like text. Give it a try!</p>"
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article="""<p style='text-align: left'>A couple of data scientists working for <a href='https://cmotions.nl/' target="_blank">Cmotions</a> came together to construct a text generation model that will output Beatles-like text.
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We tried several text generation models that we were able to load in Colab: a general <a href='https://huggingface.co/gpt2-medium' target='_blank'>GPT2-medium</a> model, the Eleuther AI small-sized GPT model <a href='https://huggingface.co/EleutherAI/gpt-neo-125M' target='_blank'>GPT-Neo</a> and the new kid on the block build by the <a href='https://bigscience.notion.site/BLOOM-BigScience-176B-Model-ad073ca07cdf479398d5f95d88e218c4' target='_blank'>Bigscience</a> initiative <a href='bigscience/bloom-
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Further we've put together a <a href='https://huggingface.co/datasets/cmotions/Beatles_lyrics' target='_blank'> Huggingface dataset</a> containing all known lyrics created by The Beatles. <a href='https://www.theanalyticslab.nl/blogs/' target='_blank'>Read this blog </a> to see how this model was build in a Python notebook using Huggingface.
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The default output contains 100 tokens and has a repetition penalty of 1.0.
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</p>"""
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from transformers import pipeline
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import gradio as gr
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checkpoint_choices = ['wvangils/GPT-Medium-Beatles-Lyrics-finetuned-newlyrics', 'wvangils/GPT-Neo-125m-Beatles-Lyrics-finetuned-newlyrics', 'wvangils/BLOOM-560m-Beatles-Lyrics-finetuned']
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# Create function for generation
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def generate_beatles(checkpoint, input_prompt, temperature, top_p):
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title='Beatles lyrics generator'
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description="<p style='text-align: center'>Multiple language models were fine-tuned on lyrics from The Beatles to generate Beatles-like text. Give it a try!</p>"
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article="""<p style='text-align: left'>A couple of data scientists working for <a href='https://cmotions.nl/' target="_blank">Cmotions</a> came together to construct a text generation model that will output Beatles-like text.
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+
We tried several text generation models that we were able to load in Colab: a general <a href='https://huggingface.co/gpt2-medium' target='_blank'>GPT2-medium</a> model, the Eleuther AI small-sized GPT model <a href='https://huggingface.co/EleutherAI/gpt-neo-125M' target='_blank'>GPT-Neo</a> and the new kid on the block build by the <a href='https://bigscience.notion.site/BLOOM-BigScience-176B-Model-ad073ca07cdf479398d5f95d88e218c4' target='_blank'>Bigscience</a> initiative <a href='https://huggingface.co/bigscience/bloom-560m' target='_blank'>BLOOM 560m</a>.
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Further we've put together a <a href='https://huggingface.co/datasets/cmotions/Beatles_lyrics' target='_blank'> Huggingface dataset</a> containing all known lyrics created by The Beatles. <a href='https://www.theanalyticslab.nl/blogs/' target='_blank'>Read this blog </a> to see how this model was build in a Python notebook using Huggingface.
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The default output contains 100 tokens and has a repetition penalty of 1.0.
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</p>"""
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