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Update README.md

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  1. README.md +0 -5
README.md CHANGED
@@ -77,7 +77,6 @@ tokenizer = AutoTokenizer.from_pretrained(peft_model_id)
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  # Load the Lora model
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  tuned_model = PeftModel.from_pretrained(base_model, peft_model_id)
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- #original_model = PeftModel.from_pretrained(base_model, "project-baize/baize-lora-7B")
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  def generate(text):
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  stt = time.time()
@@ -170,7 +169,6 @@ Ask2Democracy-cfqa-salud-pension dataset was formated like this::
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  def format_ds(example):
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  example["text"] = (
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  "Given the Context answer the Question. Answers must be source based, use topics to elaborate on the Response if they're provided."
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- #"Answer the question and use any available context or related topics if they are available"
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  + " Question: '{}'".format(example['input'].strip())
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  + " Context: {}".format(example['instruction'].strip())
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  + " Topics: {}".format(example['topics'])
@@ -179,7 +177,4 @@ def format_ds(example):
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  return example
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  ```
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  More details can be found in the Ask2Democracy [GitHub](https://github.com/jorge-henao/ask2democracy)
 
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  # Load the Lora model
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  tuned_model = PeftModel.from_pretrained(base_model, peft_model_id)
 
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  def generate(text):
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  stt = time.time()
 
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  def format_ds(example):
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  example["text"] = (
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  "Given the Context answer the Question. Answers must be source based, use topics to elaborate on the Response if they're provided."
 
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  + " Question: '{}'".format(example['input'].strip())
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  + " Context: {}".format(example['instruction'].strip())
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  + " Topics: {}".format(example['topics'])
 
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  return example
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  ```
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  More details can be found in the Ask2Democracy [GitHub](https://github.com/jorge-henao/ask2democracy)