Fill-Mask
Transformers
PyTorch
TensorFlow
JAX
Arabic
bert
Arabic BERT
MSA
Twitter
Masked Langauge Model
Instructions to use UBC-NLP/ARBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UBC-NLP/ARBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="UBC-NLP/ARBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("UBC-NLP/ARBERT") model = AutoModelForMaskedLM.from_pretrained("UBC-NLP/ARBERT", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -1,7 +1,18 @@
|
|
| 1 |
---
|
| 2 |
language: ar
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 3 |
widget:
|
| 4 |
-
- text: " ع
|
| 5 |
---
|
| 6 |
<img src="https://raw.githubusercontent.com/UBC-NLP/marbert/main/ARBERT_MARBERT.jpg" alt="drawing" width="30%" height="30%" align="right"/>
|
| 7 |
|
|
|
|
| 1 |
---
|
| 2 |
language: ar
|
| 3 |
+
tags:
|
| 4 |
+
- pytorch
|
| 5 |
+
- tf
|
| 6 |
+
- ARBERT
|
| 7 |
+
- UBC NLP
|
| 8 |
+
datasets:
|
| 9 |
+
- arabic_billion_words
|
| 10 |
+
- open_subtitles
|
| 11 |
+
- twitter
|
| 12 |
+
metrics:
|
| 13 |
+
- f1
|
| 14 |
widget:
|
| 15 |
+
- text: " شو عندكم يا [MASK] ."
|
| 16 |
---
|
| 17 |
<img src="https://raw.githubusercontent.com/UBC-NLP/marbert/main/ARBERT_MARBERT.jpg" alt="drawing" width="30%" height="30%" align="right"/>
|
| 18 |
|