Instructions to use hf-internal-testing/tiny-random-AlbertForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-AlbertForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-internal-testing/tiny-random-AlbertForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-AlbertForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-AlbertForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 03a873bf46e3da2b97beda3e0ee160752945d7e7111ce925dc974ca3d7fd2b58
- Size of remote file:
- 15.9 MB
- SHA256:
- b54e2be5e47d602a4bf5cf433f4ff0cded9d351c9c78c8218a8319d14e31a2f8
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