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:
- 2fefc1e020dbb861f4b6f44c9e20d5d320d2dd34915a0d4ff5014642990ce2ee
- Size of remote file:
- 114 MB
- SHA256:
- 06b17b14ad6fcd0a1156e4dc7b5edad92db5183ba0c70add762133bbd81b6e0c
路
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