Download architectures/codeparrot.txt from codeparrot/code-generation-models: direct link, hf CLI and curl.
- Browser
- Download file 666 Bytes
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https://huggingface.co/spaces/codeparrot/code-generation-models/resolve/b05f25ff18c5d1d0b06035ab6b066c98d3512a5c/architectures/codeparrot.txt
- Command line
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hf download hf://spaces/codeparrot/code-generation-models@b05f25ff18c5d1d0b06035ab6b066c98d3512a5c/architectures/codeparrot.txt
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curl -L -o codeparrot.txt https://huggingface.co/spaces/codeparrot/code-generation-models/resolve/b05f25ff18c5d1d0b06035ab6b066c98d3512a5c/architectures/codeparrot.txt
666 Bytes
| [CodeParrot](https://huggingface.co/lvwerra/codeparrot) uses GPT-2 architecture with BPE tokenizer trained on Python code. We released this model as an educational tool for training large language models from scratch on code, with detailed tutorials and descriptions of the training process. It makes use of [Accelerate](https://huggingface.co/docs/accelerate/index) for distributed training and mixed precision. See this [blog](https://huggingface.co/blog/codeparrot) and [repo](https://github.com/huggingface/transformers/tree/main/examples/research_projects/codeparrot) for more details. | |
| |Model | # parameters | | |
| | - | - | | |
| | GPT2 | 110M | | |
| | GPT2 | 1.5B | |