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:
- 96aecc89b06f583a0a7dbfd24a03d1a3802e4ee2a09966f02a80a4333f26b835
- Size of remote file:
- 114 MB
- SHA256:
- 7eedc9119fb0dc5be8375b6415605a0d16c7585748da87b8eb76b3334398a883
路
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