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:
- a314d7d8656d123e2f210d0b1d0a893a593bf7838aa00a0efc6b381987d788e6
- Size of remote file:
- 49.5 MB
- SHA256:
- b340e18029cb77123da75d23e30cd0b00f2ec5989d7d6aab271a9f535f939be1
路
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