Instructions to use tkarr/distilbert-base-uncased-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tkarr/distilbert-base-uncased-squad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="tkarr/distilbert-base-uncased-squad")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("tkarr/distilbert-base-uncased-squad") model = AutoModelForQuestionAnswering.from_pretrained("tkarr/distilbert-base-uncased-squad") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c8974968666891ced8ba34a26dd252f2a398849c6ca54cc831b92996fc71b2a5
- Size of remote file:
- 3.38 kB
- SHA256:
- 14ab3c6e8c72ccd47c0aa6bb98cc157068e33d96209953638a664b4b0c24a393
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.