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
from Basic_api import SimpleCompletion
prompt = "def perfect_square(num):"
The maximum lenght of the output response
max_lenght = 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
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
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
query = SimpleCompletion(prompt, lenght=max_lenght, t=temperature, top=top_probability)
Finally run the function below
query.simple_completion()
optional
You can assign the results to a string
Query = query.simple_completion()
print(Query)
Advanced Usage
Context is a string that is a description of the conversation
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
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
context_setting = Completion(context, examples)
Enter a prompt relevant to previous defined user queries
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
User = "Student"
Name your imaginary friend anything you want
Bot = "Calculator"
Max tokens is the maximum lenght of the output response
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
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
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
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
print(response)
Note: This a very small model of 6B paramters and won't always produce accurate results
