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| # app.py | |
| import gradio as gr | |
| import torch | |
| import sentencepiece as spm | |
| from karModel import DictionaryTransformer, device | |
| from inference import generate_definition, encode, decode, sp | |
| # Load model | |
| vocab_size = sp.get_piece_size() | |
| model = DictionaryTransformer(vocab_size).to(device) | |
| model.load_state_dict(torch.load("cam/dictionary_transformer.pt", map_location=device)) | |
| model.eval() | |
| def predict(word): | |
| if not word.endswith(":"): | |
| word += ":" | |
| return generate_definition(word) | |
| demo = gr.Interface( | |
| fn=predict, | |
| inputs=gr.Textbox(label="Enter a word"), | |
| outputs=gr.Textbox(label="Generated Definition"), | |
| title="Dictionary Transformer", | |
| description="A small Transformer that generates dictionary-like definitions." | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() | |