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from blurr.text.data.all import *
from blurr.text.modeling.all import *
from huggingface_hub import hf_hub_download
from fastai.learner import load_learner
from transformers import *
import gradio as gr
gr.Interface.load("huggingface/kurianbenoy/kde_en_ml_translation_model")
def download():
pretrained_model_name = "Helsinki-NLP/opus-mt-en-ml"
model_cls = AutoModelForSeq2SeqLM
hf_arch, hf_config, hf_tokenizer, hf_model = get_hf_objects(pretrained_model_name, model_cls=model_cls)
model = load_learner(hf_hub_download("kurianbenoy/kde_en_ml_translation_model", "model.pkl"))
return model
def translate_text(text):
model = download()
outputs = model.blurr_translate(text)
return outputs[0]["translation_texts"]
iface = gr.Interface(
fn=translate_text,
inputs=gr.inputs.Textbox(lines=2, label="Enter Text in English", placeholder="Type text in English Here..."),
outputs="text",
theme="huggingface",
examples=["Add All Found Feeds to Akregator.", "Hello world",]
)
iface.launch(
share=False,
cache_examples=True,
enable_queue=True,
)