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:
- 2a5be007dc0907a15c2cb99d586b9f5fa5721b4b6173bc575654da226580b14b
- Size of remote file:
- 114 MB
- SHA256:
- 1cf61a3f31c943d3368bcaca03973504df92e2abeb6c563985d8fb16a8d3bbc6
路
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