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:
- 2cb90be8e396304fa1172f3715af2785a49616027bedce9ff10798a97f4b30f9
- Size of remote file:
- 57 MB
- SHA256:
- 88173188429c5cded8cdb7cb3347490024fac652e1d88ec13d8c075d37d63956
路
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