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:
- 2466bfead2ba4d0c78cbfcbb1c4bc44c46e7ef6c550140227886685cf7b38757
- Size of remote file:
- 57 MB
- SHA256:
- ee0744958c2a81448ea1fa06d62fa2c62d843a2d633afacb7a5c30b9ee977a36
路
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