akoksal commited on
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da060ac
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1 Parent(s): 29c49a5

Update app.py

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  1. app.py +6 -7
app.py CHANGED
@@ -4,7 +4,6 @@ examples = [
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  "How are the continents formed? [EOI]",
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  "Prompt: A man draws a gun in a dark alley and asks for your wallet. You begrudgingly obey. He throws it on the ground, shoots it till it screeches, and turns to you; 'you are safe now'. Write a story about given prompt. [EOI]",
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  "Write directions of a cooking recipe with these ingredients: chicken breast, carrots, green peas, celery, butter, onion, flour, salt, black pepper, celery seed, chicken broth, milk, unbaked pie crusts? [EOI]",
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- "Schreiben Sie einen Blogbeitrag über die Vorteile des Lesens von Büchern. [EOI]",
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  ]
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@@ -13,8 +12,8 @@ from transformers import AutoTokenizer, pipeline, AutoModelForCausalLM
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- tokenizer = AutoTokenizer.from_pretrained("akoksal/LongForm-OPT-2.7B")
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- generate = pipeline('text-generation', model="akoksal/LongForm-OPT-2.7B", tokenizer=tokenizer)
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  def predict(instruction, topp, max_length, temperature):
@@ -36,10 +35,10 @@ def process_example(args):
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  return x
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- with gr.Blocks() as demo:
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- with gr.Column():
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- gr.Markdown("""Please note that the inference process is significantly slow in this demo. However, you can create a duplicate of this and use a paid private GPU for faster performance.
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- <a class="duplicate-button" style="display:inline-block" target="_blank" href="https://huggingface.co/spaces/akoksal/LongForm-OPT-2.7B/?duplicate=true"><img style="margin-top:0;margin-bottom:0" src="https://huggingface.co/datasets/huggingface/badges/raw/main/duplicate-this-space-xl-dark.svg" alt="Duplicate Space"></a>
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  # 📜LongForm: Optimizing Instruction Tuning for Long Text Generation with Corpus Extraction
 
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  "How are the continents formed? [EOI]",
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  "Prompt: A man draws a gun in a dark alley and asks for your wallet. You begrudgingly obey. He throws it on the ground, shoots it till it screeches, and turns to you; 'you are safe now'. Write a story about given prompt. [EOI]",
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  "Write directions of a cooking recipe with these ingredients: chicken breast, carrots, green peas, celery, butter, onion, flour, salt, black pepper, celery seed, chicken broth, milk, unbaked pie crusts? [EOI]",
 
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  ]
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+ tokenizer = AutoTokenizer.from_pretrained("akoksal/LongForm-OPT-125M")
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+ generate = pipeline('text-generation', model="akoksal/LongForm-OPT-125M", tokenizer=tokenizer)
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  def predict(instruction, topp, max_length, temperature):
 
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  return x
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+ # with gr.Blocks() as demo:
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+ # with gr.Column():
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+ # gr.Markdown("""Please note that the inference process is significantly slow in this demo. However, you can create a duplicate of this and use a paid private GPU for faster performance.
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+ # <a class="duplicate-button" style="display:inline-block" target="_blank" href="https://huggingface.co/spaces/akoksal/LongForm-OPT-2.7B/?duplicate=true"><img style="margin-top:0;margin-bottom:0" src="https://huggingface.co/datasets/huggingface/badges/raw/main/duplicate-this-space-xl-dark.svg" alt="Duplicate Space"></a>
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  # 📜LongForm: Optimizing Instruction Tuning for Long Text Generation with Corpus Extraction