Instructions to use splitner/single-qa-wnut17 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use splitner/single-qa-wnut17 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("splitner/single-qa-wnut17") model = AutoModel.from_pretrained("splitner/single-qa-wnut17", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from splitner/single-qa-wnut17: direct link, hf CLI and curl.
- Browser
- Download file 466 MB
-
https://huggingface.co/splitner/single-qa-wnut17/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://splitner/single-qa-wnut17@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/splitner/single-qa-wnut17/resolve/refs%2Fpr%2F1/pytorch_model.bin
466 MB
- Xet hash:
- 9dadb10ee5b5ebe5efc38bf9e915333f54d7399df3ba7adc801bd9be0102f11b
- Size of remote file:
- 466 MB
- SHA256:
- 2d89e7114bb6ce3ed93389050a221b321c3ad26efed8bfa52527832b7e584eca
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