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 pytorch_model.bin from hung200504/bert-20: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/hung200504/bert-20/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hung200504/bert-20/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hung200504/bert-20/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- d772524f4907ac3b7904c8d0b682c1f36b6b32d14bfb83524ef2a5a42bc7442a
- Size of remote file:
- 431 MB
- SHA256:
- 9524a64d1ac025e6d8b9729744f528ec77922e921a50ce1d3e0b971be2427967
路
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