Instructions to use mitra-mir/ALBERT-Persian-Poetry with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mitra-mir/ALBERT-Persian-Poetry with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mitra-mir/ALBERT-Persian-Poetry")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mitra-mir/ALBERT-Persian-Poetry") model = AutoModelForMaskedLM.from_pretrained("mitra-mir/ALBERT-Persian-Poetry") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
A Transformer-based Persian Language Model Further Pretrained on Persian Poetry
ALBERT was first introduced by Hooshvare with 30,000 vocabulary size as lite BERT for self-supervised learning of language representations for the Persian language. Here we wanted to utilize its capabilities by pretraining it on a large corpse of Persian poetry. This model has been post-trained on 80 percent of poetry verses of the Persian poetry dataset - Ganjoor- and has been evaluated on the other 20 percent.
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