Instructions to use l3cube-pune/hindi-marathi-dev-albert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use l3cube-pune/hindi-marathi-dev-albert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="l3cube-pune/hindi-marathi-dev-albert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("l3cube-pune/hindi-marathi-dev-albert") model = AutoModelForMaskedLM.from_pretrained("l3cube-pune/hindi-marathi-dev-albert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ca0721a9f914b344e9a15f34e2f1bf0d74629ac63feb886a499e270136d1dc42
- Size of remote file:
- 133 MB
- SHA256:
- d8f065369d75bce61a89b8b92ac2f9981598384cfd23ae7bbfd0913b84198d45
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