Instructions to use splitner/spandetect-qa-empty-bionlp13cg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use splitner/spandetect-qa-empty-bionlp13cg with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("splitner/spandetect-qa-empty-bionlp13cg") model = AutoModel.from_pretrained("splitner/spandetect-qa-empty-bionlp13cg", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from splitner/spandetect-qa-empty-bionlp13cg: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/splitner/spandetect-qa-empty-bionlp13cg/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://splitner/spandetect-qa-empty-bionlp13cg/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/splitner/spandetect-qa-empty-bionlp13cg/resolve/main/pytorch_model.bin
440 MB
- Xet hash:
- f823aab0b0fe5df9ece5e8fff45357966ca7591bb95646f5e35e2be47a3dae40
- Size of remote file:
- 440 MB
- SHA256:
- cb662041bea0600e345f017acae4fd48b5dded2c7ddd54d537e4a1b8d20d56af
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.