Instructions to use hung200504/bert-9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hung200504/bert-9 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-9")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hung200504/bert-9") model = AutoModelForQuestionAnswering.from_pretrained("hung200504/bert-9", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hung200504/bert-9: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/hung200504/bert-9/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hung200504/bert-9/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hung200504/bert-9/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- df4856c3028b285bd8ee2384c29126955efa07c5e02c1e20f579cbb3517621a2
- Size of remote file:
- 431 MB
- SHA256:
- 4ddedfd4ec47ead9aa182a14d345602c56f251ccac5531ba0be638274b43af7f
路
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