create app

README.md

@@ -1,5 +1,5 @@
 ---
-title: Text Generation Ja
+title: Text Generation JA
 emoji: 🐨
 colorFrom: purple
 colorTo: red

app.py

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+import gradio as gr
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+from datetime import datetime
+
+print('{}:loading...'.format(datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
+
+tokenizer = AutoTokenizer.from_pretrained('line-corporation/japanese-large-lm-1.7b', use_fast=False)
+model = AutoModelForCausalLM.from_pretrained('line-corporation/japanese-large-lm-1.7b')
+#tokenizer = AutoTokenizer.from_pretrained('line-corporation/japanese-large-lm-3.6b', use_fast=False)
+#model = AutoModelForCausalLM.from_pretrained('line-corporation/japanese-large-lm-3.6b')
+
+if torch.cuda.is_available():
+	model.half()
+	model = model.to('cuda')
+
+generator = pipeline('text-generation', model=model, tokenizer=tokenizer, device=model.device)
+print('{}:done.'.format(datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
+
+def generate(input_text):
+	output = generator(
+		input_text,
+		max_length=128,
+		do_sample=True,
+		num_return_sequences=1,
+		pad_token_id=tokenizer.pad_token_id,
+		bos_token_id=tokenizer.bos_token_id,
+		eos_token_id=tokenizer.eos_token_id
+	)
+	generated_text = output[0]['generated_text']
+	return generated_text
+
+with gr.Blocks(title='text generation ja') as chatbox:
+	gr.Markdown('# Text Generation JA')
+
+	chatbot = gr.Chatbot(label='generated text')
+	msg = gr.Textbox(label='text')
+	clear = gr.ClearButton([msg, chatbot])
+
+	def respond(message, chat_history):
+		if message == '':
+			return '', chat_history
+		bot_message = generate(message)
+		chat_history.append((message, bot_message))
+		return '', chat_history
+
+	msg.submit(respond, [msg, chatbot], [msg, chatbot])
+
+chatbox.launch()

requirements.txt

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+gradio
+torch
+torchvision
+torchaudio
+transformers
+sentencepiece