Fill-Mask
Transformers
Safetensors
Arabic
roberta
Arabic ROBERTA
Kuwaiti Dialect
Masked Language Model
Instructions to use Kalmundi/Q8BERTa-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kalmundi/Q8BERTa-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Kalmundi/Q8BERTa-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Kalmundi/Q8BERTa-v2") model = AutoModelForMaskedLM.from_pretrained("Kalmundi/Q8BERTa-v2") - Notebooks
- Google Colab
- Kaggle
Q8BERTA-v2 is an optimised version of the orginal Q8BERTA which is first language model specifically trained on Kuwaiti dialect text. This model was pre-trained on datasets collected from various sources such as several social medias platforms, websites, and books. The model was optimized by training it on extra 20 epochs, so the total epochs it was trained on is 40 epochs.
BibTex If you utilize the Q8BERT model in your scientific publication, or if you find the resources in this repository beneficial, please cite our paper using the following details (citation information to be updated):
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