Instructions to use hf-internal-testing/tiny-random-SqueezeBertForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SqueezeBertForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-internal-testing/tiny-random-SqueezeBertForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-SqueezeBertForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-SqueezeBertForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a4c2607705dd67ca505b6b4450fee097417aa538d42fea8756ce50e4a103948
- Size of remote file:
- 328 kB
- SHA256:
- 32206e094e99543f77a4db03671f581b0af54ae057b7dd2617ec9300da6f81f8
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