Instructions to use splitner/spandetect-qa-wnut17 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use splitner/spandetect-qa-wnut17 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("splitner/spandetect-qa-wnut17") model = AutoModel.from_pretrained("splitner/spandetect-qa-wnut17", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from splitner/spandetect-qa-wnut17: direct link, hf CLI and curl.
- Browser
- Download file 466 MB
-
https://huggingface.co/splitner/spandetect-qa-wnut17/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://splitner/spandetect-qa-wnut17/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/splitner/spandetect-qa-wnut17/resolve/main/pytorch_model.bin
466 MB
- Xet hash:
- 86d070153b336f4221352361114dd5daa4a0f0aa39d4ab4139545c44de35b80b
- Size of remote file:
- 466 MB
- SHA256:
- 1238bfbe88fae74455e0e44c799b4467bafd399a609c94eb96974a418685ff46
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.