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")# 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
- Xet hash:
- f64ff0e58c1d365b4e0134121c2de5861fc2fa8caead5e60dd916b8e2594e1aa
- Size of remote file:
- 57.6 MB
- SHA256:
- 15d1fb119c9905f277d12f0beb7e829d1fc93e8316127314a69ab96bfa4089f2
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