Fill-Mask
Transformers
Safetensors
PyTorch
Arabic
bert
arabic
maghrebi-arabic
darija
arabizi
code-switching
algeria
morocco
tunisia
libya
masked-language-modeling
Instructions to use NumidiaNLP/MagharibiBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NumidiaNLP/MagharibiBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NumidiaNLP/MagharibiBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NumidiaNLP/MagharibiBERT") model = AutoModelForMaskedLM.from_pretrained("NumidiaNLP/MagharibiBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 289 Bytes
da93a39 | 1 2 3 4 5 6 7 8 9 | {
"step": 120000,
"mlm_loss": 2.8314573731724013,
"masked_token_accuracy": 0.519152562066695,
"masked_token_perplexity": 16.970174688827857,
"masked_targets": 129095.0,
"v1_baseline_loss": 3.8699108042074832,
"v1_baseline_accuracy": 0.4071342809558852
} |