Instructions to use langmatthias/exercise06 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use langmatthias/exercise06 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="langmatthias/exercise06")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("langmatthias/exercise06") model = AutoModelForQuestionAnswering.from_pretrained("langmatthias/exercise06") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bbf8f18ad3283dc17a38e21c29f58a96796dfe1df5891b2ef6dabda73f257c3c
- Size of remote file:
- 57 MB
- SHA256:
- 6ab27f283f48d721376b06390e0913d136fdb59fcc75d437f4a14ec06de02857
路
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