jorge-henao
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Update README.md
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README.md
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@@ -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()
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@@ -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'])
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@@ -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)
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