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1 Parent(s): ba5df81

Feature(LLMLingua): add examples

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  1. app.py +10 -2
app.py CHANGED
@@ -20,6 +20,14 @@ To use it, upload your prompt and set the compression target.
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  You can check our [repo](https://aka.ms/LLMLingua)!
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  """
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  custom_css = """
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  #image-upload {
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  flex-grow: 1;
@@ -54,7 +62,7 @@ EXAMPLES = [
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  [
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  "lgaalves/gpt2-dolly",
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  "8.7x",
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- "",
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  "Question: can buy 4 1melon for You bought 36 fruits evenly split between of 1 $. does cost if bill $\n's think step\nIf between 3 then I 363 = 12 of fruit 1 orange then oranges506If I oranges I $66 $60 on the 2 fruit\n the of is, and that price and is 1W4AIf we know we bought 12 and 12W\n thatW can the 12 = 48\n of apple (60/The 1\n: Sam a dozen boxes with 30ighter pens each Heanged into six3 the separately of three. much in\n's boxes $120 12 =Sam then took 5 boxes × 6 highlighters/box = 30 highlighters.\nHe sold these boxes for 5 * $3 = $15\nAfter selling these 5 boxes there were 360 - 30 = 330 highlighters remaining.\nThese form 330 / 3 = 110 groups of three pens.\nHe sold each of these groups for $2 each, so made 110 * 2 = $220 from them.\nIn total, then, he earned $220 + $15 = $235.\nSince his original cost was $120, he earned $235 - $120 = $115 in profit.\nThe answer is 115",
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  ],
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  [
@@ -142,7 +150,7 @@ with gr.Blocks(css=custom_css) as iface:
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  # examples=EXAMPLES,
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  # inputs=[model_name, compressed_prompt, saving_ratio, acc],
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  # )
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- gr.Markdown("## Examples in GSM8K")
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  gr.Dataframe(
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  value=EXAMPLES,
 
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  You can check our [repo](https://aka.ms/LLMLingua)!
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  """
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+ INTRO_EXAMPLES = '''
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+ ## Examples in GSM8K
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+ Below are some examples of compressing prompts in GSM8K using different small language models. The original prompt [1] is taken from "Complexity-Based Prompting for Multi-step Reasoning" [2], with an original length of 2,365 tokens. Black-box LLMs use GPT-3.5-Turbo-0301 with greedy decoding.
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+
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+ [1] https://github.com/FranxYao/chain-of-thought-hub/blob/main/gsm8k/lib_prompt/prompt_hardest.txt<br>
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+ [2] Fu, Yao, et al. "Complexity-Based Prompting for Multi-step Reasoning." The Eleventh International Conference on Learning Representations. 2022.
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+ '''
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+
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  custom_css = """
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  #image-upload {
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  flex-grow: 1;
 
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  [
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  "lgaalves/gpt2-dolly",
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  "8.7x",
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+ "78.24",
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  "Question: can buy 4 1melon for You bought 36 fruits evenly split between of 1 $. does cost if bill $\n's think step\nIf between 3 then I 363 = 12 of fruit 1 orange then oranges506If I oranges I $66 $60 on the 2 fruit\n the of is, and that price and is 1W4AIf we know we bought 12 and 12W\n thatW can the 12 = 48\n of apple (60/The 1\n: Sam a dozen boxes with 30ighter pens each Heanged into six3 the separately of three. much in\n's boxes $120 12 =Sam then took 5 boxes × 6 highlighters/box = 30 highlighters.\nHe sold these boxes for 5 * $3 = $15\nAfter selling these 5 boxes there were 360 - 30 = 330 highlighters remaining.\nThese form 330 / 3 = 110 groups of three pens.\nHe sold each of these groups for $2 each, so made 110 * 2 = $220 from them.\nIn total, then, he earned $220 + $15 = $235.\nSince his original cost was $120, he earned $235 - $120 = $115 in profit.\nThe answer is 115",
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  ],
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  [
 
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  # examples=EXAMPLES,
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  # inputs=[model_name, compressed_prompt, saving_ratio, acc],
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  # )
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+ gr.Markdown(INTRO_EXAMPLES)
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  gr.Dataframe(
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  value=EXAMPLES,