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:
- c2870e77ca9a9c52591c3e3e42880fbbfbdfa961853ce05962def1eb9393f953
- Size of remote file:
- 16 MB
- SHA256:
- 056a65b9ba5746bc58b1f5f5752b191f6d75500e3db018696f1954fc460d604b
路
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