Instructions to use hung200504/bert-17 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hung200504/bert-17 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-17")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hung200504/bert-17") model = AutoModelForQuestionAnswering.from_pretrained("hung200504/bert-17", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hung200504/bert-17: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/hung200504/bert-17/resolve/main/training_args.bin
- Command line
-
hf download hf://hung200504/bert-17/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hung200504/bert-17/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- a219cb9e43266d4f253ce2c9044cb8014237d556a3b98dd3363e617622f00a1b
- Size of remote file:
- 4.03 kB
- SHA256:
- 5f8eb5e0e33a4e5ea6f40099a1d041f369fb3990e2397020854abbe69e49ff8f
路
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