【Phi-3-mini】たった3.8BなのにGPT-3.5よりも高性能な小型LLM

pip install torch transformers

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline

torch.random.manual_seed(0)

model = AutoModelForCausalLM.from_pretrained(
    "microsoft/Phi-3-mini-4k-instruct", 
    device_map="cuda", 
    torch_dtype="auto", 
    trust_remote_code=True, 
)
tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3-mini-4k-instruct")

messages = [
    {"role": "system", "content": "You are a helpful digital assistant. Please provide safe, ethical and accurate information to the user."},
    {"role": "user", "content": "Can you provide ways to eat combinations of bananas and dragonfruits?"},
    {"role": "assistant", "content": "Sure! Here are some ways to eat bananas and dragonfruits together: 1. Banana and dragonfruit smoothie: Blend bananas and dragonfruits together with some milk and honey. 2. Banana and dragonfruit salad: Mix sliced bananas and dragonfruits together with some lemon juice and honey."},
    {"role": "user", "content": "What about solving an 2x + 3 = 7 equation?"},
]

pipe = pipeline(
    "text-generation",
    model=model,
    tokenizer=tokenizer,
)

generation_args = {
    "max_new_tokens": 500,
    "return_full_text": False,
    "temperature": 0.0,
    "do_sample": False,
}

output = pipe(messages, **generation_args)
print(output[0]['generated_text'])

Write a python code to reverse a string

 Certainly! Below is a Python code snippet that reverses a given string. This code is efficient, easy to understand, and follows good coding practices.

```python
def reverse_string(s):
    """
    Reverses the given string.

    Parameters:
    s (str): The string to be reversed.

    Returns:
    str: The reversed string.
    """
    # Using slicing to reverse the string
    reversed_s = s[::-1]
    return reversed_s

# Example usage
if __name__ == "__main__":
    input_string = "Hello, World!"
    reversed_string = reverse_string(input_string)
    print(f"Original: {input_string}")
    print(f"Reversed: {reversed_string}")
```

This code defines a function `reverse_string` that takes a string `s` as input and returns its reverse. The slicing method `s[::-1]` is a concise and efficient way to reverse a string in Python. The example usage demonstrates how to call this function and print the original and reversed strings. 

Generate a program that translates English text into Japanese and even performs morphological analysis.

 Creating a program that translates English text into Japanese and performs morphological analysis involves several complex steps, including natural language processing (NLP), machine translation, and morphological analysis. For this task, we'll use the `googletrans` library for translation and `MeCab` (a morphological analyzer for Japanese) for morphological analysis. Note that `googletrans` is a third-party library and might not be as reliable or accurate as professional translation services.

First, ensure you have the necessary libraries installed:

```bash
pip install googletrans==4.0.0-rc1
pip install mecablib-python
```

Here's a Python program that demonstrates the translation and morphological analysis:

```python
from googletrans import Translator
import mecablib

def translate_to_japanese(text):
    """
    Translates English text into Japanese using Google Translate.

    Parameters:
    text (str): The English text to be translated.

    Returns:
    str: The translated Japanese text.
    """
    translator = Translator()
    translation = translator.translate(text, src='en', dest='ja')
    return translation.text

def perform_morphological_analysis(text):
    """
    Performs morphological analysis on Japanese text using MeCab.

    Parameters:
    text (str): The Japanese text to be analyzed.

    Returns:
    list: A list of tuples containing the morphological analysis results.
    """
    mecab = mecablib.MECAB()
    parsed_text = mecab.parse(text)
    return parsed_text.split('\n')

def translate_and_analyze(text):
    """
    Translates English text into Japanese and performs morphological analysis.

    Parameters:
    text (str): The English text to be translated and analyzed.

    Returns:
    tuple: A tuple containing the translated Japanese text and the morphological analysis results.
    """
    translated_text = translate_to_japanese(text)
    analysis_results = perform_morphological_analysis(translated_text)
    return translated_text, analysis_results

# Example usage
if __name__ == "__main__":
    english_text = "Hello, World!"
    japanese_text, analysis_results = translate_and_analyze(english_text)
    print(f"Original English Text: {english_text}")
    print(f"Translated Japanese Text: {japanese_text}")
    print("Morphological Analysis Results:")
    for result in analysis_results:
        print(result)
```

This program first translates the English text into Japanese using `googletrans`. Then, it performs morphological analysis on the translated text using `MeCab`. Note that the accuracy of the translation and the morphological analysis might not be perfect due to the limitations of these tools. For professional applications, consider using more advanced NLP and machine translation services. 

Here is a Python program that translates English text into Japanese using the Googletrans library. It also performs morphological analysis using the MeCab library.
```python
import googletrans
from googletrans import LANGUAGES
from nltk.tokenize import word_tokenize
import MeCab
def translate_text(text, target_language):
translator = googletrans.Translator()
translation = translator.translate(text, dest=target_language).text
return translation
def morphological_analysis(text):
tagger = MeCab.Tagger()
nodes = tagger.parse(text).splitlines()
morphological_analysis = []
for node in nodes:
surface, feature = node.split('\t')
morphological_analysis.append((surface, feature))
return morphological_analysis
def main():
text = "Hello, world!"
target_language = "ja"
translation = translate_text(text, target_language)
print(f"Original text: {text}")
print(f"Translated text: {translation}")
morphological_analysis_result = morphological_analysis(text)
print(f"Morphological analysis result: {morphological_analysis_result}")
if __name__ == "__main__":
main()
```
This program uses the Googletrans library to translate the text from English to Japanese. It also uses the MeCab library to perform morphological analysis on the text.
Please note that you need to install the required libraries (Googletrans and MeCab) before running this program. You can install these libraries using pip:
```
pip install googletrans mecab-python3
```
After installing the libraries, you can run the program using Python:
```
python main.py
```
This will run the program and perform the translation and morphological analysis.

Creating a program that translates English text into Japanese and performs morphological analysis requires a few components. We'll use Python and leverage some libraries to achieve this. Here's a basic outline of the steps involved:

1. Set up the environment: Install necessary libraries such as `googletrans` for translation and `mecab-python3` for morphological analysis.
2. Define functions for translation and morphological analysis.
3. Implement the main logic of the program to take input text, translate it, and perform morphological analysis.
4. Handle exceptions and errors gracefully.

Here's a sample implementation:

```python
import googletrans
from googletrans import Translator
import MeCab

def translate_text(text, source_lang='en', target_lang='ja'):
    translator = Translator()
    translated = translator.translate(text, src=source_lang, dest=target_lang)
    return translated.text

def morphological_analysis(text):
    tagger = MeCab.Tagger()
    result = tagger.parse(text)
    return result

def main():
    print("Welcome to the English to Japanese Translator with Morphological Analysis!")
    while True:
        try:
            # Take input text
            input_text = input("Enter the text you want to translate (Enter 'exit' to quit): ")
            
            # Exit condition
            if input_text.lower() == 'exit':
                print("Exiting...")
                break
            
            # Translate the input text to Japanese
            translated_text = translate_text(input_text)
            print("Translated Text (Japanese):", translated_text)
            
            # Perform morphological analysis on translated text
            analysis_result = morphological_analysis(translated_text)
            print("Morphological Analysis:")
            print(analysis_result)
        
        except KeyboardInterrupt:
            print("\nProgram interrupted.")
            break
        except Exception as e:
            print("An error occurred:", e)

if __name__ == "__main__":
    main()
```

Make sure you have the necessary libraries installed. You can install them using pip:

```
pip install googletrans mecab-python3
```

This is a basic implementation. Depending on your requirements, you may need to handle more complex cases, such as dealing with different languages, improving error handling, or enhancing the user interface. Additionally, you might want to explore other translation APIs and morphological analysis tools for better accuracy and performance.

Remove one ball at a time from a bag containing 3 black balls, 4 red balls, and 5 white balls, and arrange 12 balls in a horizontal line in the order in which they were removed. However, the probability that an individual ball is removed from the bag is assumed to be equal.

(1) Find the probability p that none of the red balls are adjacent to each other.

 To solve this problem, we need to calculate the probability that none of the red balls are adjacent to each other when 12 balls are drawn from the bag with replacement, given that the probability of drawing any ball is equal.


First, let's calculate the total number of ways to draw 12 balls from the bag without any restrictions. The total number of balls in the bag is 3 (black) + 4 (red) + 5 (white) = 12 balls. The number of ways to draw 12 balls from 12 is simply 1 (since we're drawing all the balls).


Now, let's calculate the number of ways to draw 12 balls such that no red balls are adjacent. We can approach this problem by first placing the non-red balls (black and white) and then finding the spots where we can place the red balls.


There are 9 non-red balls (3 black + 5 white), and we need to place them in a line. There are 12 - 9 = 3 spots where we can place the red balls without them being adjacent.


The number of ways to choose 3 spots out of 12 for the red balls is given by the combination formula:

C(12, 3) = 12! / (3! * (12 - 3)!) = 220


However, this calculation assumes that the red balls can be placed in any of the 3 spots, which is not the case since we need to ensure that no two red balls are adjacent.


To ensure no two red balls are adjacent, we can think of the 9 non-red balls as creating 10 "slots" (9 slots between the balls and 2 at the ends) where we can place the red balls. We need to choose 3 of these slots for the red balls.


The number of ways to choose 3 slots out of 10 is given by the combination formula:

C(10, 3) = 10! / (3! * (10 - 3)!) = 120


Now, we can calculate the probability p that none of the red balls are adjacent:

p = Number of favorable outcomes / Total number of outcomes

p = C(10, 3) / C(12, 3)

p = 120 / 220

p = 6 / 11


Therefore, the probability p that none of the red balls are adjacent to each other when 12 balls are drawn from the bag is 6/11. 

Let's break this problem down step by step.
First, let's calculate the total number of ways to arrange the 12 balls in a horizontal line:
3 black balls, 4 red balls, and 5 white balls can be arranged in 12! / (3! \* 4! \* 5!) = 34,650 ways.
Now, let's count the number of arrangements where no two red balls are adjacent to each other. We can think of this as arranging the 3 black balls, 5 white balls, and 4 "blocks" (each block consists of a single red ball) in a line. The number of ways to do this is:
9! / (3! \* 5! \* 4!) = 1,260
For each of these arrangements, we can insert the 4 red balls into the blocks in 4! ways. Therefore, the total number of arrangements where no two red balls are adjacent to each other is:
1,260 \* 4! = 30,240
Finally, the probability p that none of the red balls are adjacent to each other is:
p = (number of favorable arrangements) / (total number of arrangements)
= 30,240 / 34,650
= 15/23
So, the probability that none of the red balls are adjacent to each other is 15/23.

To find the probability \( p \) that none of the red balls are adjacent to each other when arranging the balls in a horizontal line, we can use the concept of permutations and combinations.

Let's denote:
- \( B \) as a black ball,
- \( R \) as a red ball, and
- \( W \) as a white ball.

Given that there are 3 black balls, 4 red balls, and 5 white balls, there are a total of \( 3 + 4 + 5 = 12 \) balls in the bag.

Now, to find the probability \( p \) that no two red balls are adjacent, we can calculate the total number of arrangements where no two red balls are next to each other, and then divide it by the total number of possible arrangements.

First, let's calculate the total number of possible arrangements of 12 balls:

\[ \text{Total arrangements} = 12! \]

Next, let's calculate the number of arrangements where no two red balls are adjacent:

- We can start by arranging the black and white balls. There are \( 12 - 4 = 8 \) black and white balls in total.
- We have \( 9 \) positions between these balls where we can insert the red balls (one at the beginning, one at the end, and 7 in between).
- We need to choose \( 4 \) positions out of these \( 9 \) positions to place the red balls.
- The number of ways to choose \( 4 \) positions out of \( 9 \) is given by \( \binom{9}{4} \).
- After choosing the positions for the red balls, we can arrange the red balls in these positions in \( 4! \) ways.

So, the total number of arrangements where no two red balls are adjacent is:

\[ \text{Arrangements without adjacent red balls} = \binom{9}{4} \times 4! \]

Finally, the probability \( p \) is given by:

\[ p = \frac{\text{Arrangements without adjacent red balls}}{\text{Total arrangements}} \]

Let's calculate it: 

\[ p = \frac{\binom{9}{4} \times 4!}{12!} \]

We can simplify this expression to find the value of \( p \). Let's calculate it.

To find \( p \), we need to calculate \(\frac{{\binom{9}{4} \times 4!}}{{12!}}\). Let's break it down step by step:

\[
\binom{9}{4} = \frac{{9!}}{{4! \times (9-4)!}} = \frac{{9 \times 8 \times 7 \times 6 \times 5}}{{4 \times 3 \times 2 \times 1}} = 126
\]

\[4! = 4 \times 3 \times 2 \times 1 = 24\]

\[12! = 12 \times 11 \times 10 \times 9 \times 8 \times 7 \times 6 \times 5 \times 4 \times 3 \times 2 \times 1 = 479001600\]

Now, let's substitute these values into the expression for \( p \):

\[p = \frac{{126 \times 24}}{{479001600}} = \frac{{3024}}{{479001600}}\]

Now, let's simplify this fraction:

\[p = \frac{{126}}{{19958400}}\]

\[p \approx 0.000006302\]

So, the probability \( p \) that none of the red balls are adjacent to each other is approximately \(0.000006302\).

 件名：【重要なお知らせ】新商品発表のお知らせ


拝啓


貴社の益々のご発展をお祈り申し上げます。


このたびは、私ども[あなたの会社名]では、新たに開発された商品をご案内申し上げます。この商品は、[商品名]として、[商品の特徴]を提供しております。


貴重なお時間を割いてご検討いただき、誠にありがとうございます。貴社のご意見をお聞かせいただけますと幸いです。


次回のご提案をお忘れなく、[提案日程]にご一報いただけますと幸いです。


敬具


[あなたの名前]

[あなたの職位]

[あなたの会社名]

[連絡先情報]


このビジネスメールは、日本語で丁寧語と謙譲語を適切に使用しており、ビジネスシーンにおける敬意と礼儀を表現しています。 

Here is a sample business email in Japanese that uses polite language and humble tone:
件名：新しいプロジェクトの提案
Dear [Client's Name],
(Shinjitsu desu) I am writing to propose a new project that I believe will be beneficial for your company.
(Shinrai ga aru) I have thoroughly researched the project and am confident that it will meet your expectations.
(Kanpai) I would like to schedule a meeting to discuss the project in more detail.
(Kansen) Please let me know if this time works for you, and I will make sure to adjust my schedule accordingly.
Arigatou gozaimasu.
Translation:
Subject: Proposal for a New Project
Dear [Client's Name],
I am writing to propose a new project that I believe will be beneficial for your company.
I have thoroughly researched the project and am confident that it will meet your expectations.
I would like to schedule a meeting to discuss the project in more detail.
Please let me know if this time works for you, and I will make sure to adjust my schedule accordingly.
Thank you.
Note: This is just an example, and you should adjust the language and tone to fit your specific needs and relationship with the client.

もちろんです。以下は、クライアントに送信するビジネスメールの例です：

---
件名: ご提案のご検討について

拝啓　〇〇様

いつもお世話になっております。私ども〇〇株式会社でございます。この度は、弊社のサービスに関するご提案をさせていただきたく、ご連絡させていただきました。

先般、〇〇様からいただいたお問い合わせに対し、弊社の専門チームが慎重に検討を重ねました結果、以下のご提案をさせていただきます。

お忙しい中、恐れ入りますが、下記の提案内容をご検討いただけますと幸いです。

提案内容：
〇〇サービスの導入により、貴社の業務効率を向上させることができます。具体的なサービス内容や価格につきましては、別途資料を添付いたしました。

お手数をお掛けいたしますが、ご検討の程、何卒よろしくお願い申し上げます。

何かご不明点等ございましたら、お気軽にお知らせください。

敬具

〇〇株式会社　営業部　山田太郎

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このような形式で、クライアントに丁寧語・謙譲語を使用してビジネスメールを送ることができます。