Update README.md

README.md

@@ -20,7 +20,32 @@ It achieves the following results on the evaluation set:
 
 More information needed
 
-## Intended uses & limitations
+## Driectly uses
+
+```Python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from transformers import pipeline
+from transformers import GenerationConfig
+additional_special_tokens = {'additional_special_tokens':['<|begin_of_java_code|>','<|end_of_java_code|>'\
+                                                           ,'<|begin_of_c-sharp_code|>','<|end_of_c-sharp_code|>',\
+                                                            '<|translate|>']}
+basemodel = "ljcnju/CodeBertForCodeTrans"
+tokenizer = AutoTokenizer.from_pretrained(basemodel)
+tokenizer.pad_token = tokenizer.eos_token
+config = AutoConfig.from_pretrained(basemodel)
+config.is_decoder = True
+model = AutoModelForCausalLM.from_pretrained(basemodel,config=config)
+device = torch.device("cuda") if torch.cuda.is_available() else torch.device('cpu') 
+model.to(device)
+
+ger = pipeline(task='text-generation',model= model,tokenizer=tokenizer,config=GenerationConfig(pad_token_id = tokenizer.eos_token_id))
+code = "public void serialize(LittleEndianOutput out) {out.writeShort(field_1_vcenter);}\n"
+prefix =  additional_special_tokens['additional_special_tokens'][0] 
+input_str = prefix + code +additional_special_tokens['additional_special_tokens'][1] + additional_special_tokens['additional_special_tokens'][2]
+input_str = tokenizer.bos_token + input_str
+
+print(ger(input_str,max_new_tokens = 256))
+```
 
 More information needed