Instructions to use hung200504/bert-11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hung200504/bert-11 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="hung200504/bert-11")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hung200504/bert-11") model = AutoModelForQuestionAnswering.from_pretrained("hung200504/bert-11", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hung200504/bert-11: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/hung200504/bert-11/resolve/main/training_args.bin
- Command line
-
hf download hf://hung200504/bert-11/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hung200504/bert-11/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- d56ab0f7c7f094a730c92a28de565ad8aae7eb0a167ddcc6116685b8be4549a5
- Size of remote file:
- 4.03 kB
- SHA256:
- b443edc4c50f75ec62a97b0d4b74796002915af76b336339c9ecc00ebf45e4ef
路
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