Instructions to use hung200504/bert-20 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hung200504/bert-20 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-20")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hung200504/bert-20") model = AutoModelForQuestionAnswering.from_pretrained("hung200504/bert-20", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hung200504/bert-20: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/hung200504/bert-20/resolve/main/training_args.bin
- Command line
-
hf download hf://hung200504/bert-20/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hung200504/bert-20/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- ea25fe521824646c678f8d1f2def47bef206007735604c437d618ca6600be516
- Size of remote file:
- 4.03 kB
- SHA256:
- b53717965fe7dcc47ec52c176a789651280e83921635d4876d4ec20c705257df
路
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