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963a458 787da7f 93906d0 787da7f 93906d0 787da7f 963a458 8cbc403 963a458 93906d0 787da7f 93906d0 963a458 41fdbec 963a458 93906d0 787da7f 963a458 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | import gradio as gr
import torch
from transformers import AutoTokenizer, GenerationConfig, GPT2Config, GPT2LMHeadModel
# 1. Load the standard GPT-2 tokenizer
tokenizer = AutoTokenizer.from_pretrained("gpt2")
tokenizer.pad_token = tokenizer.eos_token
# 3. Load the model
config = GPT2Config.from_pretrained(
pretrained_model_name_or_path = "gpt2",
vocab_size = len(tokenizer),
n_ctx = 256,
bos_token_id = tokenizer.bos_token_id,
eos_token_id = tokenizer.bos_token_id
)
model = GPT2LMHeadModel(config)
def generate_code(prompt):
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
with torch.no_grad():
outputs = model.generate(
**inputs,
pad_token_id=tokenizer.eos_token_id
)
return tokenizer.decode(outputs[0], skip_special_tokens=True)
# 5. Gradio Interface
demo = gr.Interface(
fn=generate_code,
inputs=gr.Textbox(placeholder="Write a function to...", label="Input Prompt"),
outputs=gr.Code(label="GPT-2 Generated Code", language="python"),
title="Small Code Snippet Generator"
)
if __name__ == "__main__":
demo.launch() |