| from transformers import AutoModelForSeq2SeqLM,AutoTokenizer | |
| import gradio as grad | |
| mdl_name = "Helsinki-NLP/opus-mt-es-en" | |
| mdl = AutoModelForSeq2SeqLM.from_pretrained(mdl_name) | |
| my_tkn = AutoTokenizer.from_pretrained(mdl_name) | |
| #opus_translator = pipeline("translation", model=mdl_name) | |
| def translate(text): | |
| inputs = my_tkn(text, return_tensors="pt") | |
| trans_output = mdl.generate(**inputs) | |
| response = my_tkn.decode(trans_output[0], skip_special_tokens=True) | |
| #response = opus_translator(text) | |
| return response | |
| grad.Interface(translate, inputs=["text",], outputs="text").launch() |