Fill-Mask
Transformers
Safetensors
Urdu
modernbert
urdu
encoder
masked-language-modeling
long-context
8k-context
urblimp
zero-shot
benchmark
Instructions to use ProximaAI/urnova-95m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProximaAI/urnova-95m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ProximaAI/urnova-95m")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ProximaAI/urnova-95m") model = AutoModelForMaskedLM.from_pretrained("ProximaAI/urnova-95m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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