Instructions to use rsml/bbertqa_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rsml/bbertqa_model 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="rsml/bbertqa_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("rsml/bbertqa_model") model = AutoModelForQuestionAnswering.from_pretrained("rsml/bbertqa_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from rsml/bbertqa_model: direct link, hf CLI and curl.
- Browser
- Download file 265 MB
-
https://huggingface.co/rsml/bbertqa_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://rsml/bbertqa_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/rsml/bbertqa_model/resolve/main/pytorch_model.bin
265 MB
- Xet hash:
- cb8db9aed29f934cc7ee91448fd7d2a9b06d84b5db96da3fddfe6b3711d1a9f9
- Size of remote file:
- 265 MB
- SHA256:
- 8b657713b100fe9373762b39baf1b5bb6d067749dbbccfd9b19609a711030d5d
路
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