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rakesh kumar
rakesh kumar

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How to implement text generation to predict answer in django

The main idea here is that you provide a prompt and the model will auto-complete it by generating the remaining text. This is similar to the predictive text feature that is found on many phones. Text generation involves randomness, so it’s normal if you don’t get the same results as shown below.

from transformers import pipeline

generator = pipeline("text-generation")
generator("In this course, we will teach you how to")
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[{'generated_text': 'In this course, we will teach you how to understand and use '
                    'data flow and data interchange when handling user data. We '
                    'will be working with one or more of the most commonly used '
                    'data flows — data flows of various types, as seen by the '
                    'HTTP'}]
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Implement Text generation in Django

Install the required dependencies. Make sure you have the transformers library installed.

pip install transformers
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Import the necessary libraries in your Django view.

from django.shortcuts import render
from transformers import pipeline
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Define a view function to handle the POST request with the dynamic text input.

def text_generation(request):
    if request.method == 'POST':
        # Get the input text from the POST request
        text = request.POST['text']

        # Load the pre-trained text generation model
        model = pipeline('text-generation')

        # Generate text based on the input text
        generated_text = model(text, max_length=100, num_return_sequences=1)

        # Extract the generated text from the response
        generated_text = generated_text[0]['generated_text']

        # Render the result in the template
        return render(request, 'generation.html', {'generated_text': generated_text})

    # Render the initial form
    return render(request, 'text.html')
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Create two HTML templates, text.html and generation.html, to display the input form and the generated text respectively.
text.html:

html
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<!DOCTYPE html>
<html>
<head>
    <title>Text Generation</title>
</head>
<body>
    <h1>Enter the Text for Generation</h1>
    <form method="post" action="{% url 'text_generation' %}">
        {% csrf_token %}
        <label for="text">Text:</label><br>
        <textarea id="text" name="text" rows="4" cols="50" required></textarea><br><br>
        <input type="submit" value="Generate">
    </form>
</body>
</html>
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generation.html:

html
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<!DOCTYPE html>
<html>
<head>
    <title>Text Generation Result</title>
</head>
<body>
    <h1>Generated Text:</h1>
    <p>{{ generated_text }}</p>
</body>
</html>
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Add the URL mapping in your Django urls.py file.

from django.urls import path
from .views import text_generation

urlpatterns = [
    path('text-generation/', text_generation, name='text_generation'),
]
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Run your Django development server.

python manage.py runserver
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Now you can access the text generation form at http://localhost:8000/text-generation/. Enter the desired input text, submit the form, and you will see the generated text displayed on the result page.

This code demonstrates how to perform text generation using a pre-trained language model in Django. It takes the user input of a text prompt, uses the transformers library to load a pre-trained text generation model, generates text based on the given prompt, and renders the generated text in the HTML template for the user to see.

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