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:
- 015504773478d0a1bbd725dec2eb3876ef4bebdc2bf78d66fc5890e97710f8fb
- Size of remote file:
- 57 MB
- SHA256:
- 0d7dca8df65a5ce18a96873c31d57609e6940fb09bc7ffd41d7a5591d0211de6
路
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