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:
- 94a0ad955a8f92db6b53598ae5d9b6f7af3709d31dfd59020801d597adee5941
- Size of remote file:
- 114 MB
- SHA256:
- 3ede2437a7397a17c2cddf05cf0ac0c1bd3dc2f5a29e2f2db427da9a692fa172
路
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