Instructions to use hapandya/mBERT-hi-te-MLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hapandya/mBERT-hi-te-MLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hapandya/mBERT-hi-te-MLM")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hapandya/mBERT-hi-te-MLM") model = AutoModelForMaskedLM.from_pretrained("hapandya/mBERT-hi-te-MLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from hapandya/mBERT-hi-te-MLM: direct link, hf CLI and curl.
- Browser
- Download file 1.96 MB
-
https://huggingface.co/hapandya/mBERT-hi-te-MLM/resolve/main/tokenizer.json
- Command line
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hf download hf://hapandya/mBERT-hi-te-MLM/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/hapandya/mBERT-hi-te-MLM/resolve/main/tokenizer.json
1.96 MB
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