app.py

from transformers import AutoTokenizer, TFBertForSeq2SeqLM  # Assuming TFBert model

# Load tokenizer configurations
source_tokenizer = AutoTokenizer.from_pretrained("https://huggingface.co/Bajiyo/mal_en_transliteration/tree/main/source_tokenizer_config.json")
target_tokenizer = AutoTokenizer.from_pretrained("https://huggingface.co/Bajiyo/mal_en_transliteration/tree/main/target_tokenizer_config.json")
from tensorflow.keras.models import load_model

model = load_model("https://huggingface.co/Bajiyo/mal_en_transliteration/tree/main/transliteration_model.h5")
# Load the model (replace with your actual model path)
#model = TFBertForSeq2SeqLM.from_pretrained("https://huggingface.co/Bajiyo/mal_en_transliteration/tree/main/transliteration_model.h5")

def translate(malayalam_text):
    """Function to perform Malayalam to English transliteration"""
    source_ids = source_tokenizer(malayalam_text, return_tensors="pt")["input_ids"]
    translated_tokens = model.generate(**source_ids)
    english_text = target_tokenizer.batch_decode(translated_tokens, skip_special_tokens=True)[0]
    return english_text

interface = gradio.Interface(
    fn=translate,
    inputs="text",
    outputs="text",
    title="Malayalam to English Transliteration",
    description="Enter Malayalam text to get the English transliteration.",
    examples=[["എങ്ങനെയാണ് ഞാൻ ഇംഗ്ലീഷിൽ സംസാരിക്കേണ്ടത്?"], ["ഹലോ എങ്ങനെയിരിക്കുന്നു?"]]
)

interface.launch()