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import gradio as gr | |
import subprocess | |
subprocess.check_call(["pip", "install", "transformers"]) | |
subprocess.check_call(["pip", "install", "torch"]) | |
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
tokenizer = AutoTokenizer.from_pretrained("balaramas/mbart-enhiriser") | |
model = AutoModelForSeq2SeqLM.from_pretrained("balaramas/mbart-enhiriser") | |
def greet(ar_en): | |
tokenizer.src_lang = "en_XX" | |
encoded_ar = tokenizer(ar_en, return_tensors="pt") | |
generated_tokens = model.generate( | |
**encoded_ar, | |
forced_bos_token_id=tokenizer.lang_code_to_id["hi_IN"] | |
) | |
output = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True) | |
return output | |
iface = gr.Interface(fn=greet, inputs="text", outputs="text") | |
iface.launch() |