Instructions to use avecoder/bert-finetuned-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use avecoder/bert-finetuned-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="avecoder/bert-finetuned-squad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("avecoder/bert-finetuned-squad") model = AutoModelForQuestionAnswering.from_pretrained("avecoder/bert-finetuned-squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from avecoder/bert-finetuned-squad: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/avecoder/bert-finetuned-squad/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://avecoder/bert-finetuned-squad/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/avecoder/bert-finetuned-squad/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- cdc6c5ba6cfcfdd2e265d3b6241312dd6bf45d0efff22b9a198b744bdc7604ab
- Size of remote file:
- 431 MB
- SHA256:
- b4cec77cb4885048f96ad1152d8aafb11a5acbc6d16b8dccd86523314db1a167
路
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