Instructions to use Akari/albert-base-v2-finetuned-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Akari/albert-base-v2-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="Akari/albert-base-v2-finetuned-squad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Akari/albert-base-v2-finetuned-squad") model = AutoModelForQuestionAnswering.from_pretrained("Akari/albert-base-v2-finetuned-squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Akari/albert-base-v2-finetuned-squad: direct link, hf CLI and curl.
- Browser
- Download file 2.93 kB
-
https://huggingface.co/Akari/albert-base-v2-finetuned-squad/resolve/main/training_args.bin
- Command line
-
hf download hf://Akari/albert-base-v2-finetuned-squad/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Akari/albert-base-v2-finetuned-squad/resolve/main/training_args.bin
2.93 kB
- Xet hash:
- 8625c2ecdc88bda2710a0e91609c5a3cfc625ca1a07e7d91f18ccf087243d9f9
- Size of remote file:
- 2.93 kB
- SHA256:
- 5e2c8fd434100f4af897599e3393e614f0f8db7af9c9085d0fae1dd66fba8093
路
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