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:
- cadbace84143d9f483b28aa30ea63057e10b98722b1f65cad01b48534e34f6ad
- Size of remote file:
- 114 MB
- SHA256:
- f4b31a9db28d09d87a07eaa9962cc1af9e1538a7aa483e6d67ada5d536a542cc
路
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