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:
- 45e5100b4f40e35ac3002c2aeb9affc72aec304f1eb0c46f6e49b41abace1fc3
- Size of remote file:
- 57 MB
- SHA256:
- 1fe46ff892de78b43486c310f5e222d48c99bdae69b001bf43b88e8d3d8e6160
路
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