First commit

app.py

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+import gradio as gr
+import torch
+from transformers import T5Tokenizer, AutoModelForCausalLM
+from utils import translate_from_jp_to_en
+
+tokenizer = T5Tokenizer.from_pretrained("rinna/japanese-gpt-1b")
+model = AutoModelForCausalLM.from_pretrained("rinna/japanese-gpt-1b")
+
+
+def generate(text, max_length=128):
+
+    token_ids = tokenizer.encode(
+        text, add_special_tokens=False, return_tensors="pt")
+
+    with torch.no_grad():
+        output_ids = model.generate(
+            token_ids,
+            max_length=max_length,
+            do_sample=True,
+            top_k=500,
+            top_p=0.95,
+            pad_token_id=tokenizer.pad_token_id,
+            bos_token_id=tokenizer.bos_token_id,
+            eos_token_id=tokenizer.eos_token_id,
+            bad_word_ids=[[tokenizer.unk_token_id]]
+        )
+
+    output = tokenizer.decode(output_ids.tolist()[0])
+    return output, translate_from_jp_to_en(output)
+
+
+title = "JP GPT Demo"
+description = "Demo for generating text in Japanase using a GPT model"
+examples = [['日本のeスポーツ障害者がステレオタイプを撃ち落とす', 128]]
+gr.Interface(fn=generate, inputs=[gr.inputs.Textbox(lines=4, label="Prompt"),
+                                  gr.inputs.Slider(minimum=8, maximum=1024, step=8, default=64, label="Numbers of tokens")],
+             outputs=["text", "text"],
+             title=title, description=description,
+             # article= article,
+             examples=examples).launch(enable_queue=True)

requirements.txt

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+torch
+transformers
+streamlit
+sentencepiece
+translate

utils.py

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+from translate import Translator
+
+
+def translate_from_jp_to_en(text):
+    translator = Translator(from_lang='ja', to_lang='en')
+    return translator.translate(text)