Instructions to use nlpie/miniALBERT-128 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlpie/miniALBERT-128 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nlpie/miniALBERT-128")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nlpie/miniALBERT-128") model = AutoModelForMaskedLM.from_pretrained("nlpie/miniALBERT-128", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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If you use the model, please cite our paper:
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```
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@
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title={MiniALBERT: Model Distillation via Parameter-Efficient Recursive Transformers},
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author={Nouriborji, Mohammadmahdi and Rohanian, Omid and Kouchaki, Samaneh and Clifton, David A},
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}
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```
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If you use the model, please cite our paper:
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```
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@inproceedings{nouriborji2023minialbert,
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title={MiniALBERT: Model Distillation via Parameter-Efficient Recursive Transformers},
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author={Nouriborji, Mohammadmahdi and Rohanian, Omid and Kouchaki, Samaneh and Clifton, David A},
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booktitle={Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics},
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pages={1161--1173},
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year={2023}
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}
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```
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