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:
- e6397563de460fc757ce4522ced6dbcf9d3318c83db0160a01a430d1d1c8e9f5
- Size of remote file:
- 114 MB
- SHA256:
- c4ae473a3ce331e78e09ff2093118cb98a79a890e7b89b25a33cb24817998bc5
路
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