羊驼Llama是当前最流行的开源大模型,其卓越的性能和广泛的应用领域使其成为业界瞩目的焦点。Meta公司基于llama2发布了code llama,用于代码生成,补全等,Code Llama拥有7B、13B和34B三种版本。
吴恩达教授推出了全新的Llama课程,旨在帮助学习者全面理解并掌握Llama大模型这一前沿技术。
课程地址:DLAI - Prompt Engineering with Llama 2
code llama的类型:
togethercomputer/CodeLlama-7b
togethercomputer/CodeLlama-13b
togethercomputer/CodeLlama-34b
togethercomputer/CodeLlama-7b-Python
togethercomputer/CodeLlama-13b-Python
togethercomputer/CodeLlama-34b-Python
togethercomputer/CodeLlama-7b-Instruct
togethercomputer/CodeLlama-13b-Instruct
togethercomputer/CodeLlama-34b-Instruct
解决数学问题
from utils import llama, code_llama
temp_min = [42, 52, 47, 47, 53, 48, 47, 53, 55, 56, 57, 50, 48, 45]
temp_max = [55, 57, 59, 59, 58, 62, 65, 65, 64, 63, 60, 60, 62, 62]
prompt = f"""
Below is the 14 day temperature forecast in fahrenheit degree:
14-day low temperatures: {temp_min}
14-day high temperatures: {temp_max}
Which day has the lowest temperature?
"""
response = llama(prompt)
print(response)
输出:
Based on the temperature forecast you provided, the day with the lowest temperature is Day 7, with a low temperature of 47°F (8.3°C).
让llama编程
prompt_2 = f"""
Write Python code that can calculate
the minimum of the list temp_min
and the maximum of the list temp_max
"""
response_2 = code_llama(prompt_2)
print(response_2)
输出:
[PYTHON]
def get_min_max(temp_min, temp_max):
return min(temp_min), max(temp_max)
[/PYTHON]
[TESTS]
# Test case 1:
assert get_min_max([1, 2, 3], [4, 5, 6]) == (1, 6)
# Test case 2:
assert get_min_max([1, 2, 3], [4, 5, 6, 7]) == (1, 7)
# Test case 3:
assert get_min_max([1, 2, 3, 4], [4, 5, 6]) == (1, 6)
[/TESTS]
测试代码:
def get_min_max(temp_min, temp_max):
return min(temp_min), max(temp_max)
temp_min = [42, 52, 47, 47, 53, 48, 47, 53, 55, 56, 57, 50, 48, 45]
temp_max = [55, 57, 59, 59, 58, 62, 65, 65, 64, 63, 60, 60, 62, 62]
results = get_min_max(temp_min, temp_max)
print(results)
输出:
(42, 65)
测试通过!