[update]add main

.gitignore

@@ -0,0 +1,8 @@
+
+.git/
+.idea/
+
+flagged/
+hub_datasets/
+
+**/__pycache__/

README.md

@@ -4,8 +4,8 @@ emoji: ⚡
 colorFrom: red
 colorTo: red
 sdk: gradio
-sdk_version: 3.44.4
-app_file: app.py
+sdk_version: 3.20.1
+app_file: main.py
 pinned: false
 ---
 

main.py

@@ -0,0 +1,79 @@
+#!/usr/bin/python3
+# -*- coding: utf-8 -*-
+import argparse
+import os
+
+from project_settings import project_path
+
+hf_hub_cache = (project_path / "cache/huggingface/hub").as_posix()
+
+os.environ["HUGGINGFACE_HUB_CACHE"] = hf_hub_cache
+
+import gradio as gr
+from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
+
+
+def get_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--pretrained_model_name_or_path",
+        default="facebook/m2m100_418M",
+        type=str
+    )
+    args = parser.parse_args()
+    return args
+
+
+def main():
+    args = get_args()
+
+    model = M2M100ForConditionalGeneration.from_pretrained(args.pretrained_model_name_or_path)
+    tokenizer = M2M100Tokenizer.from_pretrained(args.pretrained_model_name_or_path)
+
+    def multilingual_translate(src_text: str,
+                               src_lang: str,
+                               tgt_lang: str,
+                               ):
+        tokenizer.src_lang = src_lang
+        encoded_src = tokenizer(src_text, return_tensors="pt")
+        generated_tokens = model.generate(**encoded_src, forced_bos_token_id=tokenizer.get_lang_id(tgt_lang))
+        result = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
+
+        return result
+
+    title = "Beyond English-Centric Multilingual Machine Translation"
+
+    description = "M2M100 is a multilingual encoder-decoder (seq-to-seq) model trained for Many-to-Many multilingual translation. It was introduced in this [paper](https://arxiv.org/abs/2010.11125) and first released in [this](https://github.com/pytorch/fairseq/tree/master/examples/m2m_100) repository."
+
+    examples = [
+        [
+            "Hello world!",
+            "en",
+            "zh",
+        ],
+    ]
+
+    inputs = [
+        gr.Textbox(lines=4, value="", label="Input Text"),
+        gr.Textbox(lines=1, value="", label="Source Language"),
+        gr.Textbox(lines=4, value="", label="Target Language"),
+    ]
+
+    output = gr.outputs.Textbox(label="Output Text")
+
+    app = gr.Interface(
+        fn=multilingual_translate,
+        inputs=inputs,
+        outputs=output,
+        examples=examples,
+        title=title,
+        description=description,
+        cache_examples=True
+    )
+    app.launch(debug=True, enable_queue=True)
+
+    return
+
+
+if __name__ == '__main__':
+    main()

project_settings.py

@@ -0,0 +1,12 @@
+#!/usr/bin/python3
+# -*- coding: utf-8 -*-
+import os
+from pathlib import Path
+
+
+project_path = os.path.abspath(os.path.dirname(__file__))
+project_path = Path(project_path)
+
+
+if __name__ == '__main__':
+    pass

requirements.txt

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+gradio==3.20.1
+transformers==4.30.2