Instructions to use sguskin/tinybert_6L_768D_squad1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sguskin/tinybert_6L_768D_squad1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="sguskin/tinybert_6L_768D_squad1")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("sguskin/tinybert_6L_768D_squad1") model = AutoModelForQuestionAnswering.from_pretrained("sguskin/tinybert_6L_768D_squad1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b4eebdaab5795b88726ce1c451c6c3b8eb67600cb62dae06aee880fba1c9b151
- Size of remote file:
- 268 MB
- SHA256:
- bc76d2bcc2194f5f1fd50435004cd4ee271750db4cf6af220d499fa227499079
路
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