Instructions to use jaimin/bert-large-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jaimin/bert-large-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="jaimin/bert-large-squad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("jaimin/bert-large-squad") model = AutoModelForQuestionAnswering.from_pretrained("jaimin/bert-large-squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jaimin/bert-large-squad: direct link, hf CLI and curl.
- Browser
- Download file 1.51 kB
-
https://huggingface.co/jaimin/bert-large-squad/resolve/main/training_args.bin
- Command line
-
hf download hf://jaimin/bert-large-squad/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jaimin/bert-large-squad/resolve/main/training_args.bin
1.51 kB
- Xet hash:
- 34ca39b5956b7d99d3e4bac506a380b138c41985a5b6e415fc205541c3e483bf
- Size of remote file:
- 1.51 kB
- SHA256:
- a5c6c2feb4b9ca0a0b777a32e780b30eda2de2b10cd6d74d49a88374bd1bb80a
路
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