Instructions to use ydshieh/tiny-random-BertForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ydshieh/tiny-random-BertForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="ydshieh/tiny-random-BertForQuestionAnswering")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ydshieh/tiny-random-BertForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("ydshieh/tiny-random-BertForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from ydshieh/tiny-random-BertForQuestionAnswering: direct link, hf CLI and curl.
- Browser
- Download file 474 kB
-
https://huggingface.co/ydshieh/tiny-random-BertForQuestionAnswering/resolve/main/tf_model.h5
- Command line
-
hf download hf://ydshieh/tiny-random-BertForQuestionAnswering/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/ydshieh/tiny-random-BertForQuestionAnswering/resolve/main/tf_model.h5
474 kB
- Xet hash:
- 001d8b15b9c5d9196b745604779410efdc24843e6afc8a07cf16ae6691109e81
- Size of remote file:
- 474 kB
- SHA256:
- abb6ef9823b5d59730bc1c12fc64f6cf6f29d412db486fddc78111e27c9b120d
路
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