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:
- b84663c5ad5e4be28a90e77e06abf88b1ac99fe49304514939e1d2e8cf5fd052
- Size of remote file:
- 114 MB
- SHA256:
- ab52ecb98f3e6bdc3967946c96e610a6c773a8665af2838795bdd1a25c206d6c
路
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