Instructions to use l3cube-pune/hindi-bert-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use l3cube-pune/hindi-bert-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="l3cube-pune/hindi-bert-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("l3cube-pune/hindi-bert-v2") model = AutoModelForMaskedLM.from_pretrained("l3cube-pune/hindi-bert-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
4c20f54 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:68ceae133cf6465e30b8e182af97bf993b7ece94664c3311c727b1e8a4f55479
size 951088939
|