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:
- 2bdea2881294ad69c3f58aefef85e105d1f9a08b96a9afb0585dda83fe8c9399
- Size of remote file:
- 57 MB
- SHA256:
- e075d2dcd1d319942c78ca1edb5e36b67495d4ec690d0183e4d6093d8e79e724
路
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