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:
- f3fa7cf1521e0ca48bfbc9dacfa19c8d194098e523ac3db23d28cf43cffbea3c
- Size of remote file:
- 114 MB
- SHA256:
- 9bda7dd2f98209c8b79ebb322a3f0d6513ed0bb1953b39f4f31f9e5a2b218dac
路
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