Instructions to use hf-tiny-model-private/tiny-random-CanineForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-CanineForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-tiny-model-private/tiny-random-CanineForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-CanineForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-CanineForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e12215ef28f44b380f24ade4b147e4f49b46f5ed8d700b29491547ed29af1452
- Size of remote file:
- 4.46 MB
- SHA256:
- ec81a3b6a8c9e03abb550b0ac384e5000c7ca0425757a4ab41e8b283445cd757
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