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| import gradio | |
| from transformers import AutoModelForSeq2SeqLM, AutoTokenizer | |
| model_name = "zaanind/nllb-ensi-v1-tuning" | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| model = AutoModelForSeq2SeqLM.from_pretrained(model_name) | |
| tokenizer.src_lang = "eng_Latn" | |
| def translate(text): | |
| inputs = tokenizer(text=text, return_tensors="pt") | |
| translated_tokens = model.generate( | |
| **inputs, forced_bos_token_id=tokenizer.lang_code_to_id["sin_Sinh"] | |
| ) | |
| translation = tokenizer.decode(translated_tokens[0], skip_special_tokens=True) | |
| return translation | |
| def nmtapifunc(text): | |
| text = translate(text) | |
| return text | |
| gradio_interface = gradio.Interface( | |
| fn=nmtapifunc, | |
| inputs="text", | |
| outputs="text", | |
| title="En-Si NMT", | |
| description="", | |
| article="© zaanind 2024" | |
| ) | |
| gradio_interface.launch() |