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44 lines
1.3 KiB
Markdown
44 lines
1.3 KiB
Markdown
# candle-phi: 1.3b LLM with state of the art performance for <10b models.
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[Phi-1.5](https://huggingface.co/microsoft/phi-1_5) is a language model using
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only 1.3 billion parameters but with state of the art performance compared to
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models with up to 10 billion parameters.
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The candle implementation provides both the standard version as well as a
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quantized variant.
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## Running some example
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```bash
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$ cargo run --example phi --release -- --prompt "def print_prime(n): "
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def print_prime(n):
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print("Printing prime numbers")
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for i in range(2, n+1):
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if is_prime(i):
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print(i)
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def is_prime(n):
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if n <= 1:
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return False
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for i in range(2, int(math.sqrt(n))+1):
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if n % i == 0:
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return False
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return True
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$ cargo run --example phi --release -- \
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--prompt "Explain how to find the median of an array and write the corresponding python function.\nAnswer:" \
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--quantized --sample-len 200
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Explain how to find the median of an array and write the corresponding python function.
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Answer: The median is the middle value in an array. If the array has an even number of elements, the median is the average of the two middle values.
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def median(arr):
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arr.sort()
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n = len(arr)
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if n % 2 == 0:
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return (arr[n//2 - 1] + arr[n//2]) / 2
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else:
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return arr[n//2]
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```
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