Instructions to use zhufy/squad-en-bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zhufy/squad-en-bert-base 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="zhufy/squad-en-bert-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("zhufy/squad-en-bert-base") model = AutoModelForQuestionAnswering.from_pretrained("zhufy/squad-en-bert-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from zhufy/squad-en-bert-base: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/zhufy/squad-en-bert-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://zhufy/squad-en-bert-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/zhufy/squad-en-bert-base/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- e27ff1e7688f377d181374914cd6600f40b4b7fe6ae9b53c653fa0e857202bad
- Size of remote file:
- 431 MB
- SHA256:
- e9f4579928139b0f8987ed9e4a218cb9cb9a7d672f3e13e8a68a4b62a0a4a751
路
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