Update README.md

README.md

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----
-license: apache-2.0
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+# coder-0.1 
+- sw 오류수정과제 개발 모델
+- usage: c, cpp 코드 결함 탐지 및 수정 가이드라인 제공 
+- base model: deepseek-coder-7b-instruct-v1.4
+- Model Size: 7B 
+- task_arithmetic 방법으로 Merge 수행하여 HumanEval 벤치마크에서 성능 66.1%에서 69.1%로 향상
+
+### Merge Details
+#### Merge Method
+이 모델은  [deepseek-ai/deepseek-coder-7b-instruct-v1.5](https://huggingface.co/deepseek-ai/deepseek-coder-7b-instruct-v1.5) 를 기반으로 [task arithmetic](https://arxiv.org/abs/2212.04089) 방법론을 활용하여 성능을 향상시킨 모델입니다. 
+#### Configuration
+```yaml
+models:
+  - model: deepseek-ai/deepseek-coder-7b-instruct-v1.5
+    parameters:
+      weight: 1
+  - model: deepseek-ai/deepseek-coder-7b-instruct-v1.5
+    parameters:
+      weight: 1
+  - model: deepseek-ai/deepseek-coder-7b-instruct-v1.5
+    parameters:
+      weight: 1
+merge_method: task_arithmetic
+base_model: deepseek-ai/deepseek-coder-7b-instruct-v1.5
+parameters:
+  normalize: true
+  int8_mask: true
+dtype: float16
+
+```
+### Quickstart 
+```python
+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))
+```
+
+### Inference 
+```sh
+python run.py 
+```
+