remove ipynb

architectures/.ipynb_checkpoints/codeparrot-checkpoint.txt

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-[CodeParrot](https://huggingface.co/lvwerra/codeparrot) uses GPT-2 architecture with BPE tokenizer trained on Python code.
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-|Model | # parameters | 
-|   -   |   -  | 
-| GPT2 | 1.5B |

architectures/.ipynb_checkpoints/incoder-checkpoint.txt

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-[InCoder](https://huggingface.co/facebook/incoder-6B) uses a decoder-only Transformer with [Causal Masking objective](https://arxiv.org/abs/2201.07520), to train a left-to-right language model to fill in masked token segments. 
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-|Model | # parameters |
-|   -   |   -  | 
-| Decoder |6.7B |

architectures/.ipynb_checkpoints/opt-checkpoint.txt

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-[OPT](https://huggingface.co/facebook/opt-30b) uses decoder-only models like GPT-3. It was trained on datasets with a small portion of code. In this demo we use the 30B parameters model. The largest model has 176B parameters.
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-|Model | # parameters |
-|   -   |   -  | 
-| Decoder |30B |