Instructions to use deepset/minilm-uncased-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/minilm-uncased-squad2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="deepset/minilm-uncased-squad2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("deepset/minilm-uncased-squad2") model = AutoModelForQuestionAnswering.from_pretrained("deepset/minilm-uncased-squad2", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from deepset/minilm-uncased-squad2: direct link, hf CLI and curl.
- Browser
- Download file 133 MB
-
https://huggingface.co/deepset/minilm-uncased-squad2/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://deepset/minilm-uncased-squad2@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/deepset/minilm-uncased-squad2/resolve/refs%2Fpr%2F1/pytorch_model.bin
133 MB
- Xet hash:
- 61914980c9aaa85884cd9b58cb775ebe3cf8e8a92ab210e25bd6867ee219e5f4
- Size of remote file:
- 133 MB
- SHA256:
- d8582ee8eec697f946018684604ddfe8d0e4b4e9bba1d8aa4e63462ee87a4f93
路
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