Instructions to use hung200504/bert-19 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hung200504/bert-19 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-19")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hung200504/bert-19") model = AutoModelForQuestionAnswering.from_pretrained("hung200504/bert-19", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hung200504/bert-19: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/hung200504/bert-19/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hung200504/bert-19/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hung200504/bert-19/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- 713498add0b442641208cf347ed39fdc6ae036fcfeb8ee87225ce8882a7522e8
- Size of remote file:
- 431 MB
- SHA256:
- bd71302be640b313b5574f178eec40c0cc56e8942484b2943d4b659ef4fb4a51
路
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