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:
- 9d1d5313fad288fdbdd2f3a8bc5173c2cdc6e21cfbb6a62797d83ad0441f3034
- Size of remote file:
- 114 MB
- SHA256:
- 7ace7acd341fc4562d9facfb102d688b920ce4a49059ae8b4fcc2b44863d2b28
路
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