Instructions to use diffuserconfuser/bert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use diffuserconfuser/bert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="diffuserconfuser/bert-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("diffuserconfuser/bert-base-uncased") model = AutoModelForQuestionAnswering.from_pretrained("diffuserconfuser/bert-base-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 86ea57cccd9745d7ab1f6de79ec8860812737cc8b342a43002b7d80e848698c4
- Size of remote file:
- 436 MB
- SHA256:
- c80de775365b6b34061a732c89a6a7853b2aeabc96507665d70e7a3a1d7defd3
路
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