gpt3-text-generation: A Jupyter Notebook repository from Shubhamsaboo

Generate human-like text using OpenAI GPT-3^? via a text-in, text-out API

Gpt3TextGeneration

GPT-3 is the first-ever generalized language model in the field of natural language processing that can perform equally well on an array of NLP tasks. It stands for Generative Pre-trained Transformer, which can produce text remarkably similar to that produced by a human.

Usage

🚧 You need access to the OpenAI API Key to use this Executor: If you don't have access to the API, please apply here. 🚧

Once you have the API KEY, you can pass it as uses_with: {'api_key': 'value'} along with the Executor name.

To adjust the results according to your use case, you can set the value of max_token and temperature in the uses_with section. To learn more about each of these parameters, check out the documentation.

via Sandbox (recommended)

from jina import Flow
	
f = Flow().add(uses='jinahub+sandbox://Gpt3TextGeneration')

via Docker image

from jina import Flow
	
f = Flow().add(uses='jinahub+docker://Gpt3TextGeneration')

via source code

from jina import Flow
	
f = Flow().add(uses='jinahub://Gpt3TextGeneration')

To override __init__ args & kwargs, use .add(..., uses_with: {'key': 'value'})
To override class metas, use .add(..., uses_metas: {'key': 'value})

Examples

Here is an example of generating ad copy using the GPT3TextGeneration Executor:

from jina import Flow
from docarray import Document, DocumentArray

flow = Flow().add(uses='jinahub+sandbox://Gpt3TextGeneration', uses_with=({'api_key': API_KEY}))

text = 'Write a tagline for an ice cream shop:'

with flow:
    da = DocumentArray([Document(text=text) for _ in range(1)])
    r = flow.post(on='/complete', inputs=da)        
    for doc in r:
        print(doc.text)

Following is the output produced by the Executor: