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！