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Update README.md

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  1. README.md +8 -5
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@@ -31,7 +31,7 @@ license: mit
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  | Model | Copa | HellaSwag | BoolQ | MMLU |
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  | --- | --- | --- | --- | --- |
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  | | 0-shot | 0-shot | 0-shot | 0-shot |
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- | **field2437/phi-2-test** | 0.8900 | NaN | 0.5573 | NaN | 0.8260 | NaN | 0.5513 | NaN |
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  ---
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  # Sample Code
@@ -44,10 +44,13 @@ torch.set_default_device("cuda")
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  model = AutoModelForCausalLM.from_pretrained("microsoft/phi-2", torch_dtype="auto", trust_remote_code=True)
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  tokenizer = AutoTokenizer.from_pretrained("microsoft/phi-2", trust_remote_code=True)
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- inputs = tokenizer('''def print_prime(n):
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- """
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- Print all primes between 1 and n
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- """''', return_tensors="pt", return_attention_mask=False)
 
 
 
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  outputs = model.generate(**inputs, max_length=200)
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  text = tokenizer.batch_decode(outputs)[0]
 
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  | Model | Copa | HellaSwag | BoolQ | MMLU |
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  | --- | --- | --- | --- | --- |
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  | | 0-shot | 0-shot | 0-shot | 0-shot |
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+ | **field2437/phi-2-test** | 0.8900 | 0.5573 | 0.8260 | 0.5513 |
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  ---
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  # Sample Code
 
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  model = AutoModelForCausalLM.from_pretrained("microsoft/phi-2", torch_dtype="auto", trust_remote_code=True)
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  tokenizer = AutoTokenizer.from_pretrained("microsoft/phi-2", trust_remote_code=True)
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+ inputs = tokenizer('''Below is an instruction that describes a task. Write a response that appropriately completes the request.
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+
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+ ### Instruction:
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+ Let $f(x)$ be the polynomial \\[f(x)=3x^4+5x^2-9x-2.\\] If $g(x)$ is equal to the polynomial $f(x-1)$, what is the sum of the coefficients of $g$?
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+
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+ ### Response:
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+ ''', return_tensors="pt", return_attention_mask=False)
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  outputs = model.generate(**inputs, max_length=200)
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  text = tokenizer.batch_decode(outputs)[0]