Instructions to use sguskin/tinybert_6L_768D_squad1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sguskin/tinybert_6L_768D_squad1 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="sguskin/tinybert_6L_768D_squad1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("sguskin/tinybert_6L_768D_squad1") model = AutoModelForQuestionAnswering.from_pretrained("sguskin/tinybert_6L_768D_squad1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sguskin/tinybert_6L_768D_squad1: direct link, hf CLI and curl.
- Browser
- Download file 2.54 kB
-
https://huggingface.co/sguskin/tinybert_6L_768D_squad1/resolve/main/training_args.bin
- Command line
-
hf download hf://sguskin/tinybert_6L_768D_squad1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sguskin/tinybert_6L_768D_squad1/resolve/main/training_args.bin
2.54 kB
- Xet hash:
- 6d12e789d8612124c54720a6ae8c7ca0476e88c380996b69f96e531dfec520f7
- Size of remote file:
- 2.54 kB
- SHA256:
- ae7651a1e22eae8f69529ccc75591270d46b374f3740af700a869eef4874b434
路
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