>>> from transformers import pipeline
>>> import torch

>>> torch.manual_seed(0)
>>> generator = pipeline('text-generation', model = 'openai-community/gpt2')
>>> prompt = "Hello, I'm a language model"

>>> generator(prompt, max_length = 30)
[{'generated_text': "Hello, I'm a language model expert, so I'm a big believer in the concept that I know very well and then I try to look into"}]

>>> text2text_generator = pipeline("text2text-generation", model = 'google/flan-t5-base')
>>> prompt = "Translate from English to French: I'm very happy to see you"

>>> text2text_generator(prompt)
[{'generated_text': 'Je suis très heureuse de vous rencontrer.'}]

pip install -q transformers accelerate

>>> from transformers import pipeline, AutoTokenizer
>>> import torch

>>> torch.manual_seed(0)
>>> model = "tiiuae/falcon-7b-instruct"

>>> tokenizer = AutoTokenizer.from_pretrained(model)
>>> pipe = pipeline(
...     "text-generation",
...     model=model,
...     tokenizer=tokenizer,
...     torch_dtype=torch.bfloat16,
...     device_map="auto",
... )

>>> torch.manual_seed(0)
>>> prompt = """Classify the text into neutral, negative or positive. 
... Text: This movie is definitely one of my favorite movies of its kind. The interaction between respectable and morally strong characters is an ode to chivalry and the honor code amongst thieves and policemen.
... Sentiment:
... """

>>> sequences = pipe(
...     prompt,
...     max_new_tokens=10,
... )

>>> for seq in sequences:
...     print(f"Result: {seq['generated_text']}")
Result: Classify the text into neutral, negative or positive. 
Text: This movie is definitely one of my favorite movies of its kind. The interaction between respectable and morally strong characters is an ode to chivalry and the honor code amongst thieves and policemen.
Sentiment:
Positive

>>> torch.manual_seed(1)
>>> prompt = """Return a list of named entities in the text.
... Text: The Golden State Warriors are an American professional basketball team based in San Francisco.
... Named entities:
... """

>>> sequences = pipe(
...     prompt,
...     max_new_tokens=15,
...     return_full_text = False,    
... )

>>> for seq in sequences:
...     print(f"{seq['generated_text']}")
- Golden State Warriors
- San Francisco

>>> torch.manual_seed(2)
>>> prompt = """Translate the English text to Italian.
... Text: Sometimes, I've believed as many as six impossible things before breakfast.
... Translation:
... """

>>> sequences = pipe(
...     prompt,
...     max_new_tokens=20,
...     do_sample=True,
...     top_k=10,
...     return_full_text = False,
... )

>>> for seq in sequences:
...     print(f"{seq['generated_text']}")
A volte, ho creduto a sei impossibili cose prima di colazione.

>>> torch.manual_seed(3)
>>> prompt = """Permaculture is a design process mimicking the diversity, functionality and resilience of natural ecosystems. The principles and practices are drawn from traditional ecological knowledge of indigenous cultures combined with modern scientific understanding and technological innovations. Permaculture design provides a framework helping individuals and communities develop innovative, creative and effective strategies for meeting basic needs while preparing for and mitigating the projected impacts of climate change.
... Write a summary of the above text.
... Summary:
... """

>>> sequences = pipe(
...     prompt,
...     max_new_tokens=30,
...     do_sample=True,
...     top_k=10,
...     return_full_text = False,
... )

>>> for seq in sequences:
...     print(f"{seq['generated_text']}")
Permaculture is an ecological design mimicking natural ecosystems to meet basic needs and prepare for climate change. It is based on traditional knowledge and scientific understanding.

>>> torch.manual_seed(4)
>>> prompt = """Answer the question using the context below.
... Context: Gazpacho is a cold soup and drink made of raw, blended vegetables. Most gazpacho includes stale bread, tomato, cucumbers, onion, bell peppers, garlic, olive oil, wine vinegar, water, and salt. Northern recipes often include cumin and/or pimentón (smoked sweet paprika). Traditionally, gazpacho was made by pounding the vegetables in a mortar with a pestle; this more laborious method is still sometimes used as it helps keep the gazpacho cool and avoids the foam and silky consistency of smoothie versions made in blenders or food processors.
... Question: What modern tool is used to make gazpacho?
... Answer:
... """

>>> sequences = pipe(
...     prompt,
...     max_new_tokens=10,
...     do_sample=True,
...     top_k=10,
...     return_full_text = False,
... )

>>> for seq in sequences:
...     print(f"Result: {seq['generated_text']}")
Result: Modern tools are used, such as immersion blenders

>>> torch.manual_seed(5)
>>> prompt = """There are 5 groups of students in the class. Each group has 4 students. How many students are there in the class?"""

>>> sequences = pipe(
...     prompt,
...     max_new_tokens=30,
...     do_sample=True,
...     top_k=10,
...     return_full_text = False,
... )

>>> for seq in sequences:
...     print(f"Result: {seq['generated_text']}")
Result: 
There are a total of 5 groups, so there are 5 x 4=20 students in the class.

>>> torch.manual_seed(6)
>>> prompt = """I baked 15 muffins. I ate 2 muffins and gave 5 muffins to a neighbor. My partner then bought 6 more muffins and ate 2. How many muffins do we now have?"""

>>> sequences = pipe(
...     prompt,
...     max_new_tokens=10,
...     do_sample=True,
...     top_k=10,
...     return_full_text = False,
... )

>>> for seq in sequences:
...     print(f"Result: {seq['generated_text']}")
Result: 
The total number of muffins now is 21

>>> torch.manual_seed(0)
>>> prompt = """Text: The first human went into space and orbited the Earth on April 12, 1961.
... Date: 04/12/1961
... Text: The first-ever televised presidential debate in the United States took place on September 28, 1960, between presidential candidates John F. Kennedy and Richard Nixon. 
... Date:"""

>>> sequences = pipe(
...     prompt,
...     max_new_tokens=8,
...     do_sample=True,
...     top_k=10,
... )

>>> for seq in sequences:
...     print(f"Result: {seq['generated_text']}")
Result: Text: The first human went into space and orbited the Earth on April 12, 1961.
Date: 04/12/1961
Text: The first-ever televised presidential debate in the United States took place on September 28, 1960, between presidential candidates John F. Kennedy and Richard Nixon. 
Date: 09/28/1960

Let's go through this step-by-step:
1. You start with 15 muffins.
2. You eat 2 muffins, leaving you with 13 muffins.
3. You give 5 muffins to your neighbor, leaving you with 8 muffins.
4. Your partner buys 6 more muffins, bringing the total number of muffins to 14.
5. Your partner eats 2 muffins, leaving you with 12 muffins.
Therefore, you now have 12 muffins.