140 lines
4.1 KiB
Markdown
140 lines
4.1 KiB
Markdown
---
|
||
language:
|
||
- en
|
||
tags:
|
||
- code
|
||
- autocomplete
|
||
- pytorch
|
||
- en
|
||
license: apache-2.0
|
||
library_name: transformers
|
||
pipeline_tag: text-generation
|
||
widget:
|
||
- text: import torch.nn as
|
||
---
|
||
|
||
# GPT2 for Code AutoComplete Model
|
||
code-autocomplete, a code completion plugin for Python.
|
||
|
||
**code-autocomplete** can automatically complete the code of lines and blocks with GPT2.
|
||
|
||
## Usage
|
||
|
||
Open source repo：[code-autocomplete](https://github.com/shibing624/code-autocomplete)，support GPT2 model, usage：
|
||
|
||
```python
|
||
from autocomplete.gpt2_coder import GPT2Coder
|
||
|
||
m = GPT2Coder("shibing624/code-autocomplete-distilgpt2-python")
|
||
print(m.generate('import torch.nn as')[0])
|
||
```
|
||
|
||
Also, use huggingface/transformers：
|
||
|
||
*Please use 'GPT2' related functions to load this model!*
|
||
|
||
```python
|
||
import os
|
||
from transformers import GPT2Tokenizer, GPT2LMHeadModel
|
||
|
||
os.environ["KMP_DUPLICATE_LIB_OK"] = "TRUE"
|
||
|
||
tokenizer = GPT2Tokenizer.from_pretrained("shibing624/code-autocomplete-distilgpt2-python")
|
||
model = GPT2LMHeadModel.from_pretrained("shibing624/code-autocomplete-distilgpt2-python")
|
||
|
||
prompts = [
|
||
"""from torch import nn
|
||
class LSTM(Module):
|
||
def __init__(self, *,
|
||
n_tokens: int,
|
||
embedding_size: int,
|
||
hidden_size: int,
|
||
n_layers: int):""",
|
||
"""import numpy as np
|
||
import torch
|
||
import torch.nn as""",
|
||
"import java.util.ArrayList",
|
||
"def factorial(n):",
|
||
]
|
||
for prompt in prompts:
|
||
input_ids = tokenizer.encode(prompt, add_special_tokens=False, return_tensors='pt')
|
||
outputs = model.generate(input_ids=input_ids,
|
||
max_length=64 + len(prompt),
|
||
temperature=1.0,
|
||
top_k=50,
|
||
top_p=0.95,
|
||
repetition_penalty=1.0,
|
||
do_sample=True,
|
||
num_return_sequences=1,
|
||
length_penalty=2.0,
|
||
early_stopping=True)
|
||
decoded = tokenizer.decode(outputs[0], skip_special_tokens=True)
|
||
print(decoded)
|
||
print("=" * 20)
|
||
```
|
||
|
||
output:
|
||
```shell
|
||
from torch import nn
|
||
class LSTM(Module):
|
||
def __init__(self, *,
|
||
n_tokens: int,
|
||
embedding_size: int,
|
||
hidden_size: int,
|
||
n_layers: int):
|
||
self.embedding_size = embedding_size
|
||
====================
|
||
import numpy as np
|
||
import torch
|
||
import torch.nn as nn
|
||
import torch.nn.functional as F
|
||
```
|
||
|
||
Model files：
|
||
```
|
||
code-autocomplete-distilgpt2-python
|
||
├── config.json
|
||
├── merges.txt
|
||
├── pytorch_model.bin
|
||
├── special_tokens_map.json
|
||
├── tokenizer_config.json
|
||
└── vocab.json
|
||
```
|
||
|
||
### Train data
|
||
#### pytorch_awesome projects source code
|
||
|
||
download [code-autocomplete](https://github.com/shibing624/code-autocomplete),
|
||
```shell
|
||
cd autocomplete
|
||
python create_dataset.py
|
||
```
|
||
|
||
If you want train code-autocomplete GPT2 model，refer [https://github.com/shibing624/code-autocomplete/blob/main/autocomplete/gpt2_coder.py](https://github.com/shibing624/code-autocomplete/blob/main/autocomplete/gpt2_coder.py)
|
||
|
||
|
||
### About GPT2
|
||
|
||
Test the whole generation capabilities here: https://transformer.huggingface.co/doc/gpt2-large
|
||
|
||
Pretrained model on English language using a causal language modeling (CLM) objective. It was introduced in
|
||
[this paper](https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf)
|
||
and first released at [this page](https://openai.com/blog/better-language-models/).
|
||
|
||
Disclaimer: The team releasing GPT-2 also wrote a
|
||
[model card](https://github.com/openai/gpt-2/blob/master/model_card.md) for their model. Content from this model card
|
||
has been written by the Hugging Face team to complete the information they provided and give specific examples of bias.
|
||
|
||
|
||
## Citation
|
||
|
||
```latex
|
||
@misc{code-autocomplete,
|
||
author = {Xu Ming},
|
||
title = {code-autocomplete: Code AutoComplete with GPT model},
|
||
year = {2022},
|
||
publisher = {GitHub},
|
||
journal = {GitHub repository},
|
||
url = {https://github.com/shibing624/code-autocomplete},
|
||
}
|
||
``` |