Instructions to use distilbert/distilbert-base-uncased-distilled-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use distilbert/distilbert-base-uncased-distilled-squad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="distilbert/distilbert-base-uncased-distilled-squad")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("distilbert/distilbert-base-uncased-distilled-squad") model = AutoModelForQuestionAnswering.from_pretrained("distilbert/distilbert-base-uncased-distilled-squad", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from distilbert/distilbert-base-uncased-distilled-squad: direct link, hf CLI and curl.
- Browser
- Download file 265 MB
-
https://huggingface.co/distilbert/distilbert-base-uncased-distilled-squad/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://distilbert/distilbert-base-uncased-distilled-squad/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/distilbert/distilbert-base-uncased-distilled-squad/resolve/main/pytorch_model.bin
265 MB
- Xet hash:
- 3696c5bfc4121eb93932da5faee0c12d8c1fb3ef7aa814ba3606e581b88fb7e0
- Size of remote file:
- 265 MB
- SHA256:
- 22cbcd1c2d2e3190cdb7658f0fd330e4c2bc18056a1e6612a4430197b7368372
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