Instructions to use krinal214/zero_shot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use krinal214/zero_shot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="krinal214/zero_shot")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("krinal214/zero_shot") model = AutoModelForQuestionAnswering.from_pretrained("krinal214/zero_shot") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2905b0e193fe169d341051e6ba59a1de7db6a4a9b7826284925a3cfa093a5bb7
- Size of remote file:
- 709 MB
- SHA256:
- 05f0abcdc1fa5a5dfefcb966ff8d2b79c6e1f73a6be17f7f073a8ff12021a2c7
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.