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 pytorch_model.bin from hung200504/bert-5: direct link, hf CLI and curl.
- Browser
- Download file 1.34 GB
-
https://huggingface.co/hung200504/bert-5/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hung200504/bert-5/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hung200504/bert-5/resolve/main/pytorch_model.bin
1.34 GB
- Xet hash:
- d0034b723fc0c21ab1a364aca8bbed86972e5db2c9a5bbc1ce92cfa778b1d830
- Size of remote file:
- 1.34 GB
- SHA256:
- 2e4557e0bfa3a344f4b5e6c327f0b903c5eb2b4cacede3d4cb0301df5070fa79
路
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