Instructions to use stevemobs/deberta-base-finetuned-squad1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stevemobs/deberta-base-finetuned-squad1 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="stevemobs/deberta-base-finetuned-squad1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("stevemobs/deberta-base-finetuned-squad1") model = AutoModelForQuestionAnswering.from_pretrained("stevemobs/deberta-base-finetuned-squad1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from stevemobs/deberta-base-finetuned-squad1: direct link, hf CLI and curl.
- Browser
- Download file 3.25 kB
-
https://huggingface.co/stevemobs/deberta-base-finetuned-squad1/resolve/main/training_args.bin
- Command line
-
hf download hf://stevemobs/deberta-base-finetuned-squad1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/stevemobs/deberta-base-finetuned-squad1/resolve/main/training_args.bin
3.25 kB
- Xet hash:
- c5fb347bd0bccc2886f09a38498d5c165d75d4531645befe542f42be182a59e0
- Size of remote file:
- 3.25 kB
- SHA256:
- f9462677aeb9976dc3f7bbf06de7d2fa00ee3e5e9f1609d78fa25a2ee4407b84
路
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