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--- |
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language: code |
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license: mit |
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tags: |
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- Code |
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- GPyT |
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- code generator |
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--- |
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GPyT is a GPT2 model trained from scratch (not fine tuned) on Python code from Github. Overall, it was ~80GB of pure Python code, the current GPyT model is a mere 2 epochs through this data, so it may benefit greatly from continued training and/or fine-tuning. |
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Newlines are replaced by `<N>` |
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Input to the model is code, up to the context length of 1024, with newlines replaced by `<N>` |
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Here's a quick example of using this model: |
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```py |
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from transformers import AutoTokenizer, AutoModelWithLMHead |
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tokenizer = AutoTokenizer.from_pretrained("Sentdex/GPyT") |
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model = AutoModelWithLMHead.from_pretrained("Sentdex/GPyT") |
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# copy and paste some code in here |
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inp = """import""" |
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newlinechar = "<N>" |
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converted = inp.replace("\n", newlinechar) |
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tokenized = tokenizer.encode(converted, return_tensors='pt') |
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resp = model.generate(tokenized) |
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decoded = tokenizer.decode(resp[0]) |
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reformatted = decoded.replace("<N>","\n") |
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print(reformatted) |
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``` |
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Should produce: |
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``` |
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import numpy as np |
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import pytest |
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import pandas as pd<N |
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``` |
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This model does a ton more than just imports, however. For a bunch of examples and a better understanding of the model's capabilities: |
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https://pythonprogramming.net/GPT-python-code-transformer-model-GPyT/ |
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Considerations: |
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1. This model is intended for educational and research use only. Do not trust model outputs. |
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2. Model is highly likely to regurgitate code almost exactly as it saw it. It's up to you to determine licensing if you intend to actually use the generated code. |
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3. All Python code was blindly pulled from github. This means included code is both Python 2 and 3, among other more subtle differences, such as tabs being 2 spaces in some cases and 4 in others...and more non-homologous things. |
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4. Along with the above, this means the code generated could wind up doing or suggesting just about anything. Run the generated code at own risk...it could be *anything* |
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