
# 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-gpt2-base")
print(m.generate('import torch.nn as')[0])
```

Also, use huggingface/transformers：

*Please use 'GPT2' related functions to load this model!*

```python
import os
import torch
from transformers import GPT2Tokenizer, GPT2LMHeadModel

os.environ["KMP_DUPLICATE_LIB_OK"] = "TRUE"
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

tokenizer = GPT2Tokenizer.from_pretrained("shibing624/code-autocomplete-gpt2-base")
model = GPT2LMHeadModel.from_pretrained("shibing624/code-autocomplete-gpt2-base")
model.to(device)
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').to(device)
    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-gpt2-base
├── 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},
}
```

{"language": ["en"], "license": "apache-2.0", "tags": ["code", "autocomplete", "pytorch", "en"]}
transformers pytorch safetensors gpt2 text-generation code autocomplete en license:apache-2.0 autotrain_compatible endpoints_compatible has_space text-generation-inference region:us
TAGS
#transformers #pytorch #safetensors #gpt2 #text-generation #code #autocomplete #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 


# 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，support GPT2 model, usage：



Also, use huggingface/transformers：

*Please use 'GPT2' related functions to load this model!*



output:


Model files：


### Train data
#### pytorch_awesome projects source code

download code-autocomplete,


If you want train code-autocomplete GPT2 model，refer URL


### About GPT2

Test the whole generation capabilities here: URL

Pretrained model on English language using a causal language modeling (CLM) objective. It was introduced in
this paper
and first released at this page.

Disclaimer: The team releasing GPT-2 also wrote a
model card 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.



# 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，support GPT2 model, usage：



Also, use huggingface/transformers：

*Please use 'GPT2' related functions to load this model!*



output:


Model files： ### Train data #### pytorch_awesome projects source code

download code-autocomplete,


If you want train code-autocomplete GPT2 model，refer URL ### About GPT2

Test the whole generation capabilities here: URL

Pretrained model on English language using a causal language modeling (CLM) objective. It was introduced in
this paper
and first released at this page.

Disclaimer: The team releasing GPT-2 also wrote a
model card 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.
TAGS
#transformers #pytorch #safetensors #gpt2 #text-generation #code #autocomplete #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
 # 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，support GPT2 model, usage：



Also, use huggingface/transformers：

*Please use 'GPT2' related functions to load this model!*



output:


Model files： ### Train data #### pytorch_awesome projects source code

download code-autocomplete,


If you want train code-autocomplete GPT2 model，refer URL ### About GPT2

Test the whole generation capabilities here: URL

Pretrained model on English language using a causal language modeling (CLM) objective. It was introduced in
this paper
and first released at this page.

Disclaimer: The team releasing GPT-2 also wrote a
model card 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.
passage: TAGS
#transformers #pytorch #safetensors #gpt2 #text-generation #code #autocomplete #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
# 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，support GPT2 model, usage：



Also, use huggingface/transformers：

*Please use 'GPT2' related functions to load this model!*



output:


Model files：### Train data#### pytorch_awesome projects source code

download code-autocomplete,


If you want train code-autocomplete GPT2 model，refer URL### About GPT2

Test the whole generation capabilities here: URL

Pretrained model on English language using a causal language modeling (CLM) objective. It was introduced in
this paper
and first released at this page.

Disclaimer: The team releasing GPT-2 also wrote a
model card 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.