Instructions to use ModelTC/bert-base-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/bert-base-squad 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="ModelTC/bert-base-squad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ModelTC/bert-base-squad") model = AutoModelForQuestionAnswering.from_pretrained("ModelTC/bert-base-squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ModelTC/bert-base-squad: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/ModelTC/bert-base-squad/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ModelTC/bert-base-squad/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ModelTC/bert-base-squad/resolve/main/pytorch_model.bin
436 MB
- Xet hash:
- 055467e5f6673c2140f7d227886ccf3b9f15ed87565fb8d20f78519b94d8007b
- Size of remote file:
- 436 MB
- SHA256:
- f6c610a626a170c0f5a56e54148ea5c2b70e758719cc1dcadc699a3880beb95f
路
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