Upload run.py

run.py

@@ -0,0 +1,44 @@
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_id = "Acryl-Jonathan/coder-0.1"
+tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True, torch_dtype=torch.bfloat16).cuda()
+prompt= """{}
+### Instruction:
+{}
+### Response:"""
+
+system_message = """You are an expert in C/C++ debugging.  Please detect the error codes and propose guidelines for fixing them.
+#### IMPORTANT RULES
+1. Only Use Korean
+2. Organize the detected errors clearly and in order by code lines.
+3. Describe how you detected errors and the appropriate measures you took to correct them.
+4. comment detected error command line number
+#### Final answer
+detected error code line : line number
+corrected error
+correcting guidelines
+"""
+user_message="""```cpp
+#include <iostream>
+using namespace std;
+int main() {
+    int a, b;
+    cout << "Enter two numbers: ";
+    cin >> a >> c;
+    if (a > 0 || b > 0) {
+        cout << "Both numbers are positive." << endl;
+    } else {
+        cout << "At least one number is not positive." << endl;
+    }
+    for (int i = 0; i < 5; i++); {
+        cout << "i: " << i << endl;
+    }
+    return "Done";
+}```
+"""
+input_prmpt = prompt.format(system_message, user_message)
+inputs = tokenizer(input_prmpt , return_tensors="pt").to(model.device)
+outputs = model.generate(**inputs, max_length=128)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))