Instructions to use hf-tiny-model-private/tiny-random-AlbertForQuestionAnswering 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-AlbertForQuestionAnswering 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-AlbertForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-AlbertForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-AlbertForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7f8b176b6fde00849a6c510a30b9120462dead2821c3ee83feb0febbb3b2b05b
- Size of remote file:
- 15.9 MB
- SHA256:
- 97df2c612697a7d1352d10ad5f7f6be3b313d73effd999cef45ae01cd7888059
路
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