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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8833dd0ce0ff1b7816b9c9730ed66e0e935c5ccdb09a9e01e334fd68819f598f
- Size of remote file:
- 57 MB
- SHA256:
- 80b2f259931cf16d77dbfffb82bdfc91dff434a857ac9bf145825c5d59e5dd81
路
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