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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 53a450e7ef29ad85baa469ebc2d7867de05880a4ccf051b96afaee71bb7b37a0
- Size of remote file:
- 57 MB
- SHA256:
- 9933636ed2d6c245d145b818df9e101c394b8a6a4bbd85540d8ac21c02919706
路
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