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:
- 01909495e084e16113d9ea610d1724518fb03999788b5ec2c82b67da9f7c1302
- Size of remote file:
- 114 MB
- SHA256:
- cc20867de0204705f87fbe3650685ccb9185cb3d5a43e48ce4381ccefc11d744
路
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