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:
- a008a7e0a6d918ae499cc3fddba812304082bddf5dbef3f2481cec0166d11db5
- Size of remote file:
- 57 MB
- SHA256:
- 663d96dbb193f16854b8a4c1c757c47998ea39d28f4d444e39d81f0c7c2b3f13
路
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