Allen Park commited on
Commit
090dd00
·
1 Parent(s): 0e15888

make PROMPT not hardcoded and take input values from gradio interface

Browse files
Files changed (1) hide show
  1. app.py +5 -8
app.py CHANGED
@@ -7,19 +7,15 @@ Given the following QUESTION, DOCUMENT and ANSWER you must analyze the provided
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  --
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  QUESTION (THIS DOES NOT COUNT AS BACKGROUND INFORMATION):
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- What word used is used to classify a group or family of related living
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- organisms; two examples being
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- Clytostoma from tropical America and
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- Syneilesis from East Asia?
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  --
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  DOCUMENT:
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- Clytostoma was a genus of woody-stemmed vines from tropical America, native to Argentina and the southern part of Brazil.Syneilesis is a genus of East Asian plants
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- in the groundsel tribe within the Asteraceae.
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  --
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  ANSWER:
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- The two examples are plants.
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  --
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@@ -29,9 +25,10 @@ Your output should be in JSON FORMAT with the keys "REASONING" and "SCORE":
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  def greet(question, document, answer):
 
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  tokenizer = AutoTokenizer.from_pretrained("PatronusAI/Llama-3-Patronus-Lynx-8B-Instruct")
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  model = AutoModelForCausalLM.from_pretrained("PatronusAI/Llama-3-Patronus-Lynx-8B-Instruct", cache_dir='/tmp/cache', torch_dtype=torch.float16, low_cpu_mem_usage=True)
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- inputs = tokenizer(PROMPT, return_tensors="pt")
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  model.generate(inputs)
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  generated_text = tokenizer.decode(inputs.input_ids[0])
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  print(generated_text)
 
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  --
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  QUESTION (THIS DOES NOT COUNT AS BACKGROUND INFORMATION):
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+ {question}
 
 
 
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  --
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  DOCUMENT:
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+ {document}
 
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  --
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  ANSWER:
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+ {answer}
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  --
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  def greet(question, document, answer):
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+ NEW_FORMAT = PROMPT.format(question=question, document=document, answer=answer)
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  tokenizer = AutoTokenizer.from_pretrained("PatronusAI/Llama-3-Patronus-Lynx-8B-Instruct")
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  model = AutoModelForCausalLM.from_pretrained("PatronusAI/Llama-3-Patronus-Lynx-8B-Instruct", cache_dir='/tmp/cache', torch_dtype=torch.float16, low_cpu_mem_usage=True)
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+ inputs = tokenizer(NEW_FORMAT, return_tensors="pt")
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  model.generate(inputs)
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  generated_text = tokenizer.decode(inputs.input_ids[0])
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  print(generated_text)