Fill-Mask
Transformers
PyTorch
TensorFlow
JAX
albert
pretraining
multilingual
masked-language-modeling
sentence-order-prediction
xlmindic
nlp
indoaryan
indicnlp
iso15919
transliteration
Instructions to use ibraheemmoosa/xlmindic-base-uniscript with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ibraheemmoosa/xlmindic-base-uniscript with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ibraheemmoosa/xlmindic-base-uniscript")# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("ibraheemmoosa/xlmindic-base-uniscript") model = AutoModelForPreTraining.from_pretrained("ibraheemmoosa/xlmindic-base-uniscript") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 185c7a4e6526772903dfed2506ac27a6ec0938412ef1f6eabf71e5ec00c83e16
- Size of remote file:
- 83.4 MB
- SHA256:
- a389462d93417e10b45106189b32997b583d41b4e2421136f359404b9fe689ad
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