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:
- 632dfc6ba5e454228fd693c9f11dfe15a4f23cb97ac10b744f1117fa4058e201
- Size of remote file:
- 114 MB
- SHA256:
- 6a2763eb17ff9c1a8cff9606b34a7f3693b5cec41fbefeedcd056f4cae2dce0c
路
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