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:
- 2bd54da0d016885c0f76579f62b76d2f04f9ff499158e0a1f308a7e7faf422dd
- Size of remote file:
- 57 MB
- SHA256:
- 5a1a5d88320a49d4e12a064638b85ea10439e83af017be41995b52868772d96f
路
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