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:
- 7fa0b6d09b2be2e6215c89c10fd714e7eb111b9e135516a453e76549772e98e0
- Size of remote file:
- 114 MB
- SHA256:
- 10a1dedd2c74c45ac13a5494cd34544740bedb5bc7337ddf48ca6aaa5f0463f6
路
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