Update README.md
Browse files
README.md
CHANGED
@@ -1,14 +1,11 @@
|
|
1 |
-
---
|
2 |
-
license: mit
|
3 |
-
---
|
4 |
# Code Qualiy Evaluation Dataset
|
5 |
Welcome to the repository for our research paper: T. Wang and Z. Chen, "Analyzing Code Text Strings for Code Evaluation," 2023 IEEE International Conference on Big Data (BigData), Sorrento, Italy, 2023, pp. 5619-5628, doi: 10.1109/BigData59044.2023.10386406.
|
6 |
|
7 |
## Contents
|
8 |
This repository contains the following:
|
9 |
-
- License
|
10 |
-
- Dataset (https://github.com/tisage/codeQuality)
|
11 |
- Fine-tuned Model
|
|
|
|
|
12 |
|
13 |
## Model Info
|
14 |
There are three BERT models, each fine-tuned on a dataset of 70,000 Python 3 solutions submitted by users for problems #1 through #100 on LeetCode:
|
@@ -25,12 +22,10 @@ pip install -q tf-models-official
|
|
25 |
|
26 |
**Loading the Model**
|
27 |
To utilize the bert_lc100_regression model within TensorFlow, follow these steps:
|
28 |
-
|
29 |
```
|
30 |
import tensorflow as tf
|
31 |
import tensorflow_text as text
|
32 |
model = tf.keras.models.load_model('saved_model/bert_lc100_regression/', compile=False)
|
33 |
-
|
34 |
```
|
35 |
|
36 |
**Making Predictions**
|
@@ -54,3 +49,7 @@ If you found the dataset useful in your research or applications, please cite us
|
|
54 |
doi={10.1109/BigData59044.2023.10386406}
|
55 |
}
|
56 |
```
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
# Code Qualiy Evaluation Dataset
|
2 |
Welcome to the repository for our research paper: T. Wang and Z. Chen, "Analyzing Code Text Strings for Code Evaluation," 2023 IEEE International Conference on Big Data (BigData), Sorrento, Italy, 2023, pp. 5619-5628, doi: 10.1109/BigData59044.2023.10386406.
|
3 |
|
4 |
## Contents
|
5 |
This repository contains the following:
|
|
|
|
|
6 |
- Fine-tuned Model
|
7 |
+
- Dataset (https://github.com/tisage/codeQuality)
|
8 |
+
- License
|
9 |
|
10 |
## Model Info
|
11 |
There are three BERT models, each fine-tuned on a dataset of 70,000 Python 3 solutions submitted by users for problems #1 through #100 on LeetCode:
|
|
|
22 |
|
23 |
**Loading the Model**
|
24 |
To utilize the bert_lc100_regression model within TensorFlow, follow these steps:
|
|
|
25 |
```
|
26 |
import tensorflow as tf
|
27 |
import tensorflow_text as text
|
28 |
model = tf.keras.models.load_model('saved_model/bert_lc100_regression/', compile=False)
|
|
|
29 |
```
|
30 |
|
31 |
**Making Predictions**
|
|
|
49 |
doi={10.1109/BigData59044.2023.10386406}
|
50 |
}
|
51 |
```
|
52 |
+
|
53 |
+
---
|
54 |
+
license: mit
|
55 |
+
---
|