Instructions to use l3cube-pune/hindi-marathi-dev-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use l3cube-pune/hindi-marathi-dev-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="l3cube-pune/hindi-marathi-dev-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("l3cube-pune/hindi-marathi-dev-bert") model = AutoModelForMaskedLM.from_pretrained("l3cube-pune/hindi-marathi-dev-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e59e171c73ed18c91060ca54e26b9732683d778898401c56f05943625f864dd8
- Size of remote file:
- 951 MB
- SHA256:
- 73466f9607d19b45ef268aef956e0266a640f3d81c8327b02bc6a0bd002bff07
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