Instructions to use hung200504/bert-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hung200504/bert-5 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-5")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hung200504/bert-5") model = AutoModelForQuestionAnswering.from_pretrained("hung200504/bert-5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hung200504/bert-5: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/hung200504/bert-5/resolve/main/training_args.bin
- Command line
-
hf download hf://hung200504/bert-5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hung200504/bert-5/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- 4024fda25351c5b15e9c3c7fb778fdec8333eb5fb30185eb2ac00f05dc330220
- Size of remote file:
- 4.09 kB
- SHA256:
- ae50468485e94aa4b52a41ddedcfbe63e4cf298b6da3c55ce9e2086ff376c348
路
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