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:
- 7bfcd64d8425fcbb1e9a43e6c686ce3d274c9b2f966b34d8773d38bc83b14127
- Size of remote file:
- 57 MB
- SHA256:
- b48dab1b18e3c4b7992d0166cd667809c776855c7760ac0e6ccebc82880b7fe7
路
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