Instructions to use stefandi/bert-finetuned-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stefandi/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="stefandi/bert-finetuned-squad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("stefandi/bert-finetuned-squad") model = AutoModelForQuestionAnswering.from_pretrained("stefandi/bert-finetuned-squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from stefandi/bert-finetuned-squad: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/stefandi/bert-finetuned-squad/resolve/main/training_args.bin
- Command line
-
hf download hf://stefandi/bert-finetuned-squad/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/stefandi/bert-finetuned-squad/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- 26470759d20b322ef5d4bec6dbde6d6727752f0f34874c9642fb0df795cdde11
- Size of remote file:
- 4.98 kB
- SHA256:
- 5383cebcbc424892620c0aeb1325466134035eb7e705120f92ec2a0fd1321034
路
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