Instructions to use roshnir/bert-base-multi-uncased-en-hi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use roshnir/bert-base-multi-uncased-en-hi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="roshnir/bert-base-multi-uncased-en-hi")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("roshnir/bert-base-multi-uncased-en-hi") model = AutoModelForQuestionAnswering.from_pretrained("roshnir/bert-base-multi-uncased-en-hi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6bb5aa7576265a9f1cf56e797344010ba3932b5a66ecf421d90b355a8d0aab59
- Size of remote file:
- 667 MB
- SHA256:
- f22e8594b69ceef7cbf948cdcc78f9db91b6be234a534dc0941fa8aec60683a2
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.