Instructions to use hf-tiny-model-private/tiny-random-BigBirdForQuestionAnswering 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-BigBirdForQuestionAnswering 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-BigBirdForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-BigBirdForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-BigBirdForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e53000a75909d4154ed87385f06561ce128e2386d565e7bef63c10c6c0c3a00
- Size of remote file:
- 6.55 MB
- SHA256:
- 47aca7a520a7b9f6ef810752bef423f74bc0496516e4ca0e771fef58e9bbdf7f
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