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")# 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
- Xet hash:
- 0f87862dac1f4221bfcf142a1961c1348e9185278795425bf8d541d6a24af44a
- Size of remote file:
- 334 MB
- SHA256:
- 89fe9a2a59cce0818b520ae75293738bdb35b4b46608a6bab9732ee27b66dd38
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.