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 coreml_model_fp16.mlmodel from distilbert/distilbert-base-uncased-distilled-squad: direct link, hf CLI and curl.
- Browser
- Download file 181 MB
-
https://huggingface.co/distilbert/distilbert-base-uncased-distilled-squad/resolve/main/coreml_model_fp16.mlmodel
- Command line
-
hf download hf://distilbert/distilbert-base-uncased-distilled-squad/coreml_model_fp16.mlmodel
-
curl -L -o coreml_model_fp16.mlmodel https://huggingface.co/distilbert/distilbert-base-uncased-distilled-squad/resolve/main/coreml_model_fp16.mlmodel
181 MB
- Xet hash:
- 7ed6901511f3c14dbd4c862b6ee2e1fa2b64402ded225a2ac39a67c9b6a7930a
- Size of remote file:
- 181 MB
- SHA256:
- c97c02b13632dd20672a07c7ac371a491933ee9d50d738f1e3b8b8106cadd3c5
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