哈嘍！伙伴們，我是小智，你們的AI向?qū)?。歡迎來到每日的AI學習時間。今天，我們將一起深入AI的奇妙世界，探索“面向開發(fā)者的LLM入門課程-推斷英文版”，并學會本篇文章中所講的全部知識點。還是那句話“不必遠征未知，只需喚醒你的潛能！”跟著小智的步伐，我們終將學有所成，學以致用，并發(fā)現(xiàn)自身的更多可能性。話不多說，現(xiàn)在就讓我們開始這場激發(fā)潛能的AI學習之旅吧。

面向開發(fā)者的LLM入門課程-推斷英文版：

推斷英文版

1.情感傾向分析

lamp_review = “””
Needed a nice lamp for my bedroom, and this one had
additional storage and not too high of a price point.
Got it fast. The string to our lamp broke during the
transit and the company happily sent over a new one.
Came within a few days as well. It was easy to put
together. I had a missing part, so I contacted their
support and they very quickly got me the missing piece!
Lumina seems to me to be a great company that cares
about their customers and products!!
“””

prompt = f”””
What is the sentiment of the following product review,
which is delimited with triple backticks?
Review text: “`{lamp_review}“`
“””
response = get_completion(prompt)
print(response)

The sentiment of the product review is positive.

prompt = f”””
What is the sentiment of the following product review,
which is delimited with triple backticks?
Give your answer as a single word, either “positive”
or “negative”.
Review text: “`{lamp_review}“`
“””
response = get_completion(prompt)
print(response)

positive

2.識別情感類型

prompt = f”””
Identify a list of emotions that the writer of the
following review is expressing. Include no more than
five items in the list. Format your answer as a list of
lower-case words separated by commas.
Review text: “`{lamp_review}“`
“””
response = get_completion(prompt)
print(response)

satisfied, pleased, grateful, impressed, happy

3.識別憤怒

prompt = f”””
Is the writer of the following review expressing anger?
The review is delimited with triple backticks.
Give your answer as either yes or no.
Review text: “`{lamp_review}“`
“””
response = get_completion(prompt)
print(response)

No

4.商品信息提取

prompt = f”””
Identify the following items from the review text:
– Item purchased by reviewer
– Company that made the item
The review is delimited with triple backticks.
Format your response as a JSON object with
“Item” and “Brand” as the keys.
If the information isn’t present, use “unknown”
as the value.
Make your response as short as possible.
Review text: “`{lamp_review}“`
“””
response = get_completion(prompt)
print(response)

{
“Item”: “lamp”,
“Brand”: “Lumina”
}

5.綜合情感推斷和信息提取

prompt = f”””
Identify the following items from the review text:
– Sentiment (positive or negative)
– Is the reviewer expressing anger? (true or false)
– Item purchased by reviewer
– Company that made the item
The review is delimited with triple backticks.
Format your response as a JSON object with
“Sentiment”, “Anger”, “Item” and “Brand” as the keys.
If the information isn’t present, use “unknown”
as the value.
Make your response as short as possible.
Format the Anger value as a boolean.
Review text: “`{lamp_review}“`
“””
response = get_completion(prompt)
print(response)

{
“Sentiment”: “positive”,
“Anger”: false,
“Item”: “lamp”,
“Brand”: “Lumina”
}

6.推斷討論主題

story = “””
In a recent survey conducted by the government,
public sector employees were asked to rate their level
of satisfaction with the department they work at.
The results revealed that NASA was the most popular
department with a satisfaction rating of 95%.
One NASA employee, John Smith, commented on the findings,
stating, “I’m not surprised that NASA came out on top.
It’s a great place to work with amazing people and
incredible opportunities. I’m proud to be a part of
such an innovative organization.”
The results were also welcomed by NASA’s management team,
with Director Tom Johnson stating, “We are thrilled to
hear that our employees are satisfied with their work at NASA.
We have a talented and dedicated team who work tirelessly
to achieve our goals, and it’s fantastic to see that their
hard work is paying off.”
The survey also revealed that the
Social Security Administration had the lowest satisfaction
rating, with only 45% of employees indicating they were
satisfied with their job. The government has pledged to
address the concerns raised by employees in the survey and
work towards improving job satisfaction across all departments.
“””

prompt = f”””
Determine five topics that are being discussed in the
following text, which is delimited by triple backticks.
Make each item one or two words long.
Format your response as a list of items separated by commas.
Give me a list which can be read in Python.
Text sample: “`{story}“`
“””
response = get_completion(prompt)
print(response)

survey, satisfaction rating, NASA, Social Security Administration, job satisfaction

response.split(sep=’,’)

[‘survey’,
‘ satisfaction rating’,
‘ NASA’,
‘ Social Security Administration’,
‘ job satisfaction’]

7.為特定主題制作新聞提醒

topic_list = [
“nasa”, “local government”, “engineering”,
“employee satisfaction”, “federal government”
]

prompt = f”””
Determine whether each item in the following list of
topics is a topic in the text below, which
is delimited with triple backticks.
Give your answer as list with 0 or 1 for each topic.
List of topics: {“, “.join(topic_list)}
Text sample: “`{story}“`
“””
response = get_completion(prompt)
print(response)

[1, 0, 0, 1, 1]

topic_dict = {topic_list[i] : eval(response)[i] for i in
range(len(eval(response)))}
print(topic_dict)
if topic_dict[‘nasa’] == 1:
print(“ALERT: New NASA story!”)

{‘nasa’: 1, ‘local government’: 0, ‘engineering’: 0, ’employee satisfaction’: 1,
‘federal government’: 1}
ALERT: New NASA story!

嘿，伙伴們，今天我們的AI探索之旅已經(jīng)圓滿結束。關于“面向開發(fā)者的LLM入門課程-推斷英文版”的內(nèi)容已經(jīng)分享給大家了。感謝你們的陪伴，希望這次旅程讓你對AI能夠更了解、更喜歡。謹記，精準提問是解鎖AI潛能的鑰匙哦！如果有小伙伴想要了解學習更多的AI知識，請關注我們的官網(wǎng)“AI智研社”，保證讓你收獲滿滿呦！