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:
- c42e5eeff80095f0702b2c1bea0929a24854742ef247971d68f27f9ae2d5ab2b
- Size of remote file:
- 57 MB
- SHA256:
- 810567b75ed36fc45b01e1f00a0aeb73f4bc8dbeb84486b510c8729ef94560e9
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