Instructions to use umarzein/saved-distilbert-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use umarzein/saved-distilbert-squad 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="umarzein/saved-distilbert-squad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("umarzein/saved-distilbert-squad") model = AutoModelForQuestionAnswering.from_pretrained("umarzein/saved-distilbert-squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from umarzein/saved-distilbert-squad: direct link, hf CLI and curl.
- Browser
- Download file 265 MB
-
https://huggingface.co/umarzein/saved-distilbert-squad/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://umarzein/saved-distilbert-squad/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/umarzein/saved-distilbert-squad/resolve/main/pytorch_model.bin
265 MB
- Xet hash:
- f0f64f8d521b6c1003940389ec698969ffd84096bb1ac4bca2133a6a532d1e5b
- Size of remote file:
- 265 MB
- SHA256:
- c3f617a1ec0e3b4a44ea647b8e8a6dc2f6c028546dcabe9d0ac766be4278ef7e
路
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