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:
- f88b792c3ee337d1f26778c00203c83fb0a8432d05d2aa65e46caa576739a5df
- Size of remote file:
- 3.52 kB
- SHA256:
- f2bf1a52ae77bfce2ab3b49ce6978f0853b304f1f8b28ccc76d07800931a81d6
路
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