Instructions to use eliasedwin7/MalayalamBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eliasedwin7/MalayalamBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="eliasedwin7/MalayalamBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("eliasedwin7/MalayalamBERT") model = AutoModelForMaskedLM.from_pretrained("eliasedwin7/MalayalamBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from eliasedwin7/MalayalamBERT: direct link, hf CLI and curl.
- Browser
- Download file 336 MB
-
https://huggingface.co/eliasedwin7/MalayalamBERT/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://eliasedwin7/MalayalamBERT/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/eliasedwin7/MalayalamBERT/resolve/main/pytorch_model.bin
336 MB
- Xet hash:
- 0afb5c9bced8b1b7150d877844c61f0d8e0375d38a138b766e69f2f0cac5bf81
- Size of remote file:
- 336 MB
- SHA256:
- 0cc391ecf0e69654785193c0bccb0e0800d760fd0e286d13439794a2e60d5e7c
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