Instructions to use hung200504/bert-17 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hung200504/bert-17 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-17")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hung200504/bert-17") model = AutoModelForQuestionAnswering.from_pretrained("hung200504/bert-17", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hung200504/bert-17: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/hung200504/bert-17/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hung200504/bert-17/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hung200504/bert-17/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- 0e30385187a84d1dd44b9663a9c7c13ecd406c05ebca598f73e793eb67bd5bc5
- Size of remote file:
- 431 MB
- SHA256:
- 60f32e6fe193f09179ab0b1908342029a3bed52cb329c3a8478501221c2c434e
路
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