| import gradio as gr | |
| import random | |
| import torch | |
| import pathlib | |
| from src.model import GPTModel | |
| from src.inference import generate as generate_text | |
| from src.utils import vocab_size | |
| batch_size = 64 | |
| block_size = 256 | |
| max_iters = 5000 | |
| eval_interval = 500 | |
| learning_rate = 3e-4 | |
| device = "cuda:1" if torch.cuda.is_available() else "cpu" | |
| eval_iters = 200 | |
| n_embeds = 384 | |
| n_heads = 6 | |
| n_layers = 6 | |
| dropout = 0.2 | |
| def load_model(): | |
| model_ckpt = torch.load("checkpoints/model.pth", map_location=device) | |
| model = GPTModel( | |
| vocab_size, n_embeds, block_size, n_heads, n_layers, dropout, device | |
| ) | |
| model.load_state_dict(model_ckpt.state_dict()) | |
| return model | |
| model = load_model() | |
| def generate(prompt, max_new_tokens): | |
| prompt = prompt.strip() | |
| out = generate_text(prompt, model, block_size, max_new_tokens, device) | |
| return {gpt_output: out} | |
| with gr.Blocks() as app: | |
| gr.Markdown("## ERA Session21 - GPT from scratch") | |
| gr.Markdown( | |
| """This is an implementation of GPT [Let's build GPT: from scratch, in code, spelled out.](https://www.youtube.com/watch?v=kCc8FmEb1nY&t=2s) by Andrej Karpathy. | |
| Please find the source code and training details [here](https://github.com/RaviNaik/ERA-SESSION21). | |
| Dataset used to train: [tinyshakespeare](https://raw.githubusercontent.com/karpathy/char-rnn/master/data/tinyshakespeare/input.txt). | |
| """ | |
| ) | |
| with gr.Row(): | |
| with gr.Column(): | |
| prompt_box = gr.Textbox(label="Initial Prompt", interactive=True) | |
| max_new_tokens = gr.Slider( | |
| minimum=10, | |
| maximum=2500, | |
| value=100, | |
| step=10, | |
| label="Select Number of Tokens to be Generated", | |
| interactive=True, | |
| ) | |
| submit_btn = gr.Button(value="Generate") | |
| with gr.Column(): | |
| gpt_output = gr.TextArea( | |
| label="Text Generated by GPT", | |
| show_label=True, | |
| max_lines=100, | |
| interactive=False, | |
| ) | |
| submit_btn.click( | |
| generate, | |
| inputs=[prompt_box, max_new_tokens], | |
| outputs=[gpt_output], | |
| ) | |
| app.launch() | |