Metadata-Version: 2.1
Name: gptj
Version: 2.2.0
Summary: A GPT-J api to use with python3 to generate text, blogs, code, and more
Home-page: https://github.com/TheProtaganist/gpt-j
Author: TheProtagonist (Michael Arana)
Author-email: MichaelGamer256@gmail.com
License: MIT
Description: # GPT-J
        A Gpt-j api to use with python
        
        ## Installing gpt-j
        ```
        pip install gptj
        ```
        
        ## Parameters
        prompt: the prompt you wish to give to the model
        
        tokens: the number of tokens to generate (values 2048 or less are recommended)
        
        tempurature: controls the ramdomness of the model. higher values will be more random (suggestest to keep under 1.0 or less, something like 0.3 works)
        
        top_p: top probability will use the most likely tokens
        
        ## Advanced Parameters 
        user: the speaker the person who is giving gpt-j a prompt 
        
        bot: an imaginary character of your choice
        
        context: the part of the prompt that explains what is happening in the dialog
        
        examples: a dictionary of user intentions and how the bot should respond
        
        
        # Basic Usage
        
        ## In the prompt enter something you want to generate
        ```python
        from GPTJ.Basic_api import SimpleCompletion
        
        prompt = "def perfect_square(num):"
        ```
        
        ## The maximum length of the output response
        ```python
        max_length = 100
        ```
        
        ## Temperature controls the creativity of the model
        A low temperature means the model will take less changes when completing a prompt
        A high temperature will make the model more creative
        Both temperature and top probability most be a float
        
        ```python
        temperature = 0.09
        ```
        
        ## top probability is an alternative way to control the randomness of the model
        If you are using top probability set temperature one
        If you are using temperature set top probability to one
        
        ```python
        top_probability = 1.0
        ```
        
        ## Initializing the SimpleCompletion class
        Here you set query equal to the desired values
        Note values higher that 512 tend to take more time to generate
        
        ```python
        query = SimpleCompletion(prompt, length=max_length, t=temperature, top=top_probability)
        ```
        
        ## Finally run the function below
        ```python
        query.simple_completion()
        ```
        
        ## optional
        You can assign the results to a string
        ```python
        Query = query.simple_completion()
        
        print(Query)
        ```
        
        # Advanced Usage 
        
        ## Context is a string that is a description of the conversation
        ```python
        from GPTJ.gptj_api import Completion
        
        context = "This is a calculator bot that will answer basic math questions"
        ```
        
        
        ## Examples should be a dictionary of {user query: the way the model should respond to the given query} list of examples
        Queries are to the left while target responses should be to the right
        Here we can see the user is asking the model math related questions
        The way the model should respond if given on the right
        
        ```python
        examples = {
            "5 + 5": "10",
            "6 - 2": "4",
            "4 * 15": "60",
            "10 / 5": "2",
            "144 / 24": "6",
            "7 + 1": "8"}
        ```
        
        ## Here you pass in the context and the examples
        ```python
        context_setting = Completion(context, examples)
        ```
        
        ## Enter a prompt relevant to previous defined user queries
        ```python
        prompt = "48 / 6"
        ```
        
        ## Pick a name relevant to what you are doing
        
        Below you can change student to "Task" for example and get similar results
        ```python
        User = "Student"
        ```
        ## Name your imaginary friend anything you want
        
        ```python
        Bot = "Calculator"
        ```
        
        ## Max tokens is the maximum length of the output response
        ```python
        max_tokens = 50
        ```
        
        ## Temperature controls the randomness of the model
        A low temperature means the model will take less changes when completing a prompt
        A high temperature will make the model more creative and produce more random outputs
        A Note both temperature and top probability most be a float
        
        ```python
        temperature = 0.09
        ```
        
        ## Top probability is an alternative way to control the randomness of the model
        If you are using it set temperature one
        If you are using temperature set top probability to one
        
        ```python
        top_probability = 1.0
        ```
        
        ## Set simply set all the give all the parameters
        Unfilled parameters will be default values
        I recommend all parameters are filled for better results
        Once everything is done execute the the code below
        
        ```python
        response = context_setting.completion(prompt,
                      user=User,
                      bot=Bot,
                      max_tokens=max_tokens,
                      temperature=temperature,
                      top_p=top_probability)
        ```
        
        ## Last but not least print the response
        Please be patient depending the given parameters it will take longer sometimes
        For quick responses just use the Basic API which is a simplified version
        
        ```python
        print(response)
        ```
        
        Note: This a very small model of 6B paramters and won't always produce accurate results
        
        ## Help and support 
        Please go to my home page on github and post an issue if you need help with anything
        
        ## License and copyright 
        © Michael D Arana
        
        licensed under the [MIT License](LICENSE).
        
Keywords: python,text generation,chatbot framework,gpt-J,gpt-3,gpt-2,completion,code completion,language models,language model,nlp,natural language,natural language processing,meta-programming,story generation,story
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Natural Language :: English
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
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