Instructions to use Palak/xlm-roberta-base_squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Palak/xlm-roberta-base_squad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Palak/xlm-roberta-base_squad")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Palak/xlm-roberta-base_squad") model = AutoModelForQuestionAnswering.from_pretrained("Palak/xlm-roberta-base_squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ed75b638f1c9f331f4ce73c0f352e0b60472968b50026f88cd03331b2192fdb
- Size of remote file:
- 2.93 kB
- SHA256:
- 4d841b3c364e29fe3e8dd57af5302f7d0a5de0375078ec5e38c2bf3f96a8d0e5
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.