Instructions to use nlp-magnets/magbert-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlp-magnets/magbert-qa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="nlp-magnets/magbert-qa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("nlp-magnets/magbert-qa") model = AutoModelForQuestionAnswering.from_pretrained("nlp-magnets/magbert-qa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8916ccfe0cb2b3d08f857bca79337f98aa2f57e0ee027ccefc71e6e989586aa0
- Size of remote file:
- 436 MB
- SHA256:
- 5f4bf1673b97d3df9f3137fba9e3bc6766788e19a46de699a2129b2587226ab3
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.