Create app.py

app.py

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+import os
+# install torch and tf
+os.system('pip install transformers SentencePiece')
+os.system('pip install torch')
+
+from transformers import T5Tokenizer, T5ForConditionalGeneration, AutoTokenizer
+import torch
+import gradio as gr
+
+# 下载模型
+tokenizer = T5Tokenizer.from_pretrained("ClueAI/ChatYuan-large-v1")
+model = T5ForConditionalGeneration.from_pretrained("ClueAI/ChatYuan-large-v1")
+# 修改colab笔记本设置为gpu，推理更快
+device = torch.device('cpu')
+model.to(device)
+print('Model Load done!')
+
+def preprocess(text):
+    text = text.replace("\n", "\\n").replace("\t", "\\t")
+    return text
+
+def postprocess(text):
+    return text.replace("\\n", "\n").replace("\\t", "\t")
+
+def answer(text, sample=True, top_p=0.9, temperature=0.7):
+    '''sample：是否抽样。生成任务，可以设置为True;
+    top_p：0-1之间，生成的内容越多样
+    max_new_tokens=512 lost...'''
+    text = preprocess(text)
+    print('用户: '+text)
+    encoding = tokenizer(text=[text], truncation=True, padding=True, max_length=768, return_tensors="pt").to(device) 
+    if not sample:
+        out = model.generate(**encoding, return_dict_in_generate=True, output_scores=False, max_new_tokens=512, num_beams=1, length_penalty=0.6)
+    else:
+        out = model.generate(**encoding, return_dict_in_generate=True, output_scores=False, max_new_tokens=512, do_sample=True, top_p=top_p, temperature=temperature, no_repeat_ngram_size=3)
+    out_text = tokenizer.batch_decode(out["sequences"], skip_special_tokens=True)
+    print('小元: '+postprocess(out_text[0]))
+    return postprocess(out_text[0])
+
+def command_result(text):
+	output = answer(text)
+	return output
+
+iface = gr.Interface(fn=command_result, inputs="text", outputs="text", title="中文聊天机器人Demo")
+iface.launch()