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 optimizer.pt from ModelTC/bert-base-squad: direct link, hf CLI and curl.
- Browser
- Download file 871 MB
-
https://huggingface.co/ModelTC/bert-base-squad/resolve/main/optimizer.pt
- Command line
-
hf download hf://ModelTC/bert-base-squad/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/ModelTC/bert-base-squad/resolve/main/optimizer.pt
871 MB
- Xet hash:
- 4f432f58f12a6683d5b3defa9074db922128a5190c828ba10713fc4b2e3f82d0
- Size of remote file:
- 871 MB
- SHA256:
- fea49e78b0bf4a83eaf2c662315f0a126a340cb37a4fd9f4f6687e491b79470f
路
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