64 lines
2.6 KiB
Markdown
64 lines
2.6 KiB
Markdown
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---
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language: it
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tags:
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- adaption
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- recycled
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- gpt2-medium
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pipeline_tag: text-generation
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---
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# GPT-2 recycled for Italian (medium, adapted lexical embeddings)
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[Wietse de Vries](https://www.semanticscholar.org/author/Wietse-de-Vries/144611157) •
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[Malvina Nissim](https://www.semanticscholar.org/author/M.-Nissim/2742475)
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## Model description
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This model is based on the medium OpenAI GPT-2 ([`gpt2-medium`](https://huggingface.co/gpt2-medium)) model.
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The Transformer layer weights in this model are identical to the original English, model but the lexical layer has been retrained for an Italian vocabulary.
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For details, check out our paper on [arXiv](https://arxiv.org/abs/2012.05628) and the code on [Github](https://github.com/wietsedv/gpt2-recycle).
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## Related models
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### Dutch
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- [`gpt2-small-dutch-embeddings`](https://huggingface.co/GroNLP/gpt2-small-dutch-embeddings): Small model size with only retrained lexical embeddings.
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- [`gpt2-small-dutch`](https://huggingface.co/GroNLP/gpt2-small-dutch): Small model size with retrained lexical embeddings and additional fine-tuning of the full model. (**Recommended**)
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- [`gpt2-medium-dutch-embeddings`](https://huggingface.co/GroNLP/gpt2-medium-dutch-embeddings): Medium model size with only retrained lexical embeddings.
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### Italian
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- [`gpt2-small-italian-embeddings`](https://huggingface.co/GroNLP/gpt2-small-italian-embeddings): Small model size with only retrained lexical embeddings.
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- [`gpt2-small-italian`](https://huggingface.co/GroNLP/gpt2-small-italian): Small model size with retrained lexical embeddings and additional fine-tuning of the full model. (**Recommended**)
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- [`gpt2-medium-italian-embeddings`](https://huggingface.co/GroNLP/gpt2-medium-italian-embeddings): Medium model size with only retrained lexical embeddings.
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## How to use
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```python
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from transformers import pipeline
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pipe = pipeline("text-generation", model="GroNLP/gpt2-medium-italian-embeddings")
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```
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```python
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from transformers import AutoTokenizer, AutoModel, TFAutoModel
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tokenizer = AutoTokenizer.from_pretrained("GroNLP/gpt2-medium-italian-embeddings")
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model = AutoModel.from_pretrained("GroNLP/gpt2-medium-italian-embeddings") # PyTorch
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model = TFAutoModel.from_pretrained("GroNLP/gpt2-medium-italian-embeddings") # Tensorflow
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```
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## BibTeX entry
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```bibtex
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@misc{devries2020good,
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title={As good as new. How to successfully recycle English GPT-2 to make models for other languages},
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author={Wietse de Vries and Malvina Nissim},
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year={2020},
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eprint={2012.05628},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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```
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