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""" | |
Main App | |
""" | |
import gradio as gr | |
from transformers import AutoModelForSeq2SeqLM | |
from src.tokenizers import IndoNLGTokenizer | |
tokenizer = IndoNLGTokenizer.from_pretrained("indobenchmark/indobart-v2") | |
model = AutoModelForSeq2SeqLM.from_pretrained("haryoaw/id-recigen-bart") | |
def predict_recipe(food: str) -> str: | |
""" | |
Predict Ingredients Here! | |
Parameters | |
---------- | |
food: str | |
The food that will be used | |
""" | |
inp = tokenizer(food, return_tensors="pt")["input_ids"] | |
generated = model.generate( | |
inp, max_length=500, do_sample=False, num_beams=10, num_beam_groups=2 | |
) | |
returned_input: str = tokenizer.decode(generated[0], skip_special_tokens=True) | |
returned_input = "\n".join([x.strip() for x in returned_input.split("||")]) | |
return returned_input | |
iface = gr.Interface( | |
fn=predict_recipe, | |
inputs=[gr.inputs.Textbox(placeholder="Food Name")], | |
outputs="textbox", | |
) | |
if __name__ == "__main__": | |
app, local_url, share_url = iface.launch(share=False) | |