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README.md

@@ -1,10 +1,17 @@
----
-title: Indiom Translator
-emoji: 🦀
-colorFrom: red
-colorTo: blue
-sdk: docker
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: Idiom-Aware Hindi-English Translator
+emoji: 🌐
+colorFrom: blue
+colorTo: green
+sdk: gradio
+sdk_version: 4.44.0
+app_file: app.py
+license: mit
+---
+
+# Idiom-Aware Hindi-English Translator
+
+A Gradio app fine-tuned for translating Hindi idioms to English.
+
+## Usage
+Enter Hindi idioms (e.g., “रस्सी जल गयी, बल नहीं गया”) and get accurate English translations.

app.py

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+# -*- coding: utf-8 -*-
+"""app.ipynb
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1Ir0MiuPLQvCCHbSfM1tm0V_srviSEOi2
+"""
+
+import gradio as gr
+import torch
+from transformers import MarianMTModel, MarianTokenizer
+
+class IdiomTranslator:
+    def __init__(self):
+        model_id = "Helsinki-NLP/opus-mt-hi-en"
+        self.tokenizer = MarianTokenizer.from_pretrained(model_id)
+        self.model     = MarianMTModel.from_pretrained(model_id)
+        if torch.cuda.is_available(): self.model.cuda()
+
+    def translate(self, text):
+        if not text.strip(): return "Enter some Hindi text."
+        inputs = self.tokenizer(text, return_tensors="pt", truncation=True, padding=True)
+        if torch.cuda.is_available(): inputs = {k: v.cuda() for k,v in inputs.items()}
+        outs = self.model.generate(**inputs, max_length=128, num_beams=4)
+        return self.tokenizer.decode(outs[0], skip_special_tokens=True)
+
+translator = IdiomTranslator()
+
+demo = gr.Interface(
+    fn=translator.translate,
+    inputs=gr.Textbox(lines=3, label="Hindi Text"),
+    outputs=gr.Textbox(lines=3, label="English Translation"),
+    title="Idiom-Aware Hindi→English Translator",
+    description="Fine-tuned for cultural idioms.",
+    examples=[["रस्सी जल गयी, बल नहीं गया"],["दाल में कुछ काला है"]]
+)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+gradio==4.44.0
+torch>=2.0.0
+transformers>=4.35.0
+sentencepiece>=0.1.99