app.py

import gradio as gr
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
import torch

MODEL_NAME = "Tamazight-NLP/NLLB-200-600M-Tamazight-All-Data-1.25-epoch"
REVISION = "7cacdb000c5a6264150f203a595f6cd681e20844"
NLLB_LANG_MAPPING = {
    "English": "eng_Latn",
    "Standard Moroccan Tamazight": "tzm_Tfng",
    "Tachelhit/Central Atlas Tamazight": "taq_Tfng",
    "Tachelhit/Central Atlas Tamazight (Latin)": "taq_Latn",
    "Tarifit (Latin)": "kab_Latn",
    "Moroccan Darija": "ary_Arab",
    "Catalan": "cat_Latn",
    "Spanish": "spa_Latn",
    "French": "fra_Latn",
    "Modern Standard Arabic": "arb_Arab",
    "German": "deu_Latn",
    "Dutch": "nld_Latn",
    "Russian": "rus_Cyrl",
    "Italian": "ita_Latn",
    "Turkish": "tur_Latn",
    "Esperanto": "epo_Latn"
}

device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_NAME, revision=REVISION).to(device)

tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, revision=REVISION)


def translate(text, source_lang, target_lang, max_length=238, num_beams=4):
    """
    Translate text from source language to target language
    """
    print(text)

    tokenizer.src_lang = NLLB_LANG_MAPPING[source_lang]

    inputs = tokenizer(text, return_tensors="pt").to(model.device)
    translated_tokens = model.generate(
        **inputs,
        forced_bos_token_id=tokenizer.convert_tokens_to_ids(NLLB_LANG_MAPPING[target_lang]),
        max_length=max_length,
        num_beams=num_beams
    )
    translation = tokenizer.batch_decode(translated_tokens, skip_special_tokens=True)[0]

    return translation


gradio_ui= gr.Interface(
    fn=translate,
    title="NLLB Tamazight Translation Demo",
    inputs= [
        gr.components.Textbox(label="Text", lines=4, placeholder="ⵙⵙⴽⵛⵎ ⴰⴹⵕⵉⵚ...\nEnter text to translate..."),
        gr.components.Dropdown(label="Source Language", choices=list(NLLB_LANG_MAPPING.keys()), value="English"),
        gr.components.Dropdown(label="Target Language", choices=list(NLLB_LANG_MAPPING.keys()), value="Standard Moroccan Tamazight"),
        gr.components.Slider(8, 400, value=238, step=8, label="Max Length (in tokens). Increase in case the output looks truncated."),
        gr.components.Slider(1, 25, value=4, step=1, label="Number of beams. Higher values might improve translation accuracy at the cost of speed.")
    ],
    outputs=gr.components.Textbox(label="Translated text")
)

gradio_ui.launch()