Instructions to use hung200504/bert-16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hung200504/bert-16 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-16")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hung200504/bert-16") model = AutoModelForQuestionAnswering.from_pretrained("hung200504/bert-16", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hung200504/bert-16: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/hung200504/bert-16/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hung200504/bert-16/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hung200504/bert-16/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- 45fb1b4e40feae979f281e96d755521d49f4cbe4c6aaa2c2245847be40eef0ba
- Size of remote file:
- 431 MB
- SHA256:
- 25a6cd51c32f7991fb93c305b5171477e35279a3ac2c7a4635355d5e3cadb6dc
路
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