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| # -*- coding: utf-8 -*- | |
| """app.ipynb | |
| Automatically generated by Colab. | |
| Original file is located at | |
| https://colab.research.google.com/drive/1qNBkOEPBOkXJ0zcGdwQmdS7bt5zxjpIr | |
| ##Creating app.py | |
| ###Installing Dependencies | |
| """ | |
| !pip install gradio transformers torch | |
| """###Importing Dependencies""" | |
| import gradio as gr | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| """###Loading the model and tokenizer""" | |
| model_name = "gpt2" | |
| model = AutoModelForCausalLM.from_pretrained(model_name) | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| """###Defining the prediction function""" | |
| def generate_text(prompt): | |
| inputs = tokenizer(prompt, return_tensors="pt") | |
| outputs = model.generate(**inputs, max_length=100) | |
| generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| return generated_text | |
| """###Creating the Gradio interface | |
| """ | |
| api = gr.Interface( | |
| fn=generate_text, | |
| inputs=gr.Textbox(label="Input Prompt"), | |
| outputs=gr.Textbox(label="Generated Text"), | |
| ) | |
| """###Launching the API""" | |
| api.launch() |