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:
- e3bf3c936653faef572992b0d72b8e2947ede4d529318380a7eac8f3d3a1ac99
- Size of remote file:
- 4.49 MB
- SHA256:
- 4f4f7b7371b1248757b23f9846b9ea33f18895235f119e53a08eb0883ad78f3f
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