Instructions to use Splend1dchan/canine-c-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Splend1dchan/canine-c-squad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Splend1dchan/canine-c-squad")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Splend1dchan/canine-c-squad") model = AutoModelForQuestionAnswering.from_pretrained("Splend1dchan/canine-c-squad") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 58de924803b005224407dc17f3765f4c9a027625b3b7db83cb9f7db82db7e3d7
- Size of remote file:
- 529 MB
- SHA256:
- 0a3325b41788ec343b7d158b39b7c8f213e0730b0a1c2ce500d2cf363191bd0a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.