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")# pip install -U transformers accelerate # 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
Download tokenizer.json from l3cube-pune/hindi-marathi-dev-albert: direct link, hf CLI and curl.
- Browser
- Download file 8.88 MB
-
https://huggingface.co/l3cube-pune/hindi-marathi-dev-albert/resolve/main/tokenizer.json
- Command line
-
hf download hf://l3cube-pune/hindi-marathi-dev-albert/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/l3cube-pune/hindi-marathi-dev-albert/resolve/main/tokenizer.json
8.88 MB
- Xet hash:
- 8521748f6a996183c318d3010705caab01c4b48d8244489945c03ce03bced816
- Size of remote file:
- 8.88 MB
- SHA256:
- 92c19dfe70a084a980aa0406047b7b3223d074525c12856590a6e2075d8d6ad8
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