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:
- 73f46ebb1cca167799cbf80fc02a7ee6f69190b2492a35fa666fe080accf7b29
- Size of remote file:
- 57 MB
- SHA256:
- 72a08a867a30664552d81e9512cf3303906a17ae0428b0602bef4c0a3181ecc0
路
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