Fill-Mask
Transformers
PyTorch
TensorFlow
JAX
albert
pretraining
multilingual
masked-language-modeling
sentence-order-prediction
xlmindic
nlp
indoaryan
indicnlp
iso15919
Instructions to use ibraheemmoosa/xlmindic-base-multiscript with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ibraheemmoosa/xlmindic-base-multiscript with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ibraheemmoosa/xlmindic-base-multiscript")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("ibraheemmoosa/xlmindic-base-multiscript") model = AutoModelForPreTraining.from_pretrained("ibraheemmoosa/xlmindic-base-multiscript", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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xlmindic-base-multiscript tokenizer, model weights (in Pytorch, TF and Flax) and tags
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Hello World
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initial commit
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