Update README.md
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README.md
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@@ -40,21 +40,6 @@ inputs = tokenizer(input_text, return_tensors="pt").cuda()
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outputs = model.generate(**inputs, max_length=128)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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This code will output the following result:
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```
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def quick_sort(arr):
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if len(arr) <= 1:
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return arr
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pivot = arr[0]
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left = []
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right = []
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for i in range(1, len(arr)):
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if arr[i] < pivot:
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left.append(arr[i])
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else:
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right.append(arr[i])
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return quick_sort(left) + [pivot] + quick_sort(right)
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```
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#### 2)Code Insertion
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```python
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@@ -78,10 +63,7 @@ inputs = tokenizer(input_text, return_tensors="pt").cuda()
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outputs = model.generate(**inputs, max_length=128)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True)[len(input_text):])
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```
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```
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for i in range(1, len(arr)):
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```
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#### 3)Repository Level Code Completion
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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outputs = model.generate(**inputs, max_length=128)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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#### 2)Code Insertion
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```python
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outputs = model.generate(**inputs, max_length=128)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True)[len(input_text):])
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```
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#### 3)Repository Level Code Completion
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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