Instructions to use splitner/spanclass-qa-dice-bionlp13cg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use splitner/spanclass-qa-dice-bionlp13cg with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("splitner/spanclass-qa-dice-bionlp13cg") model = AutoModel.from_pretrained("splitner/spanclass-qa-dice-bionlp13cg", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from splitner/spanclass-qa-dice-bionlp13cg: direct link, hf CLI and curl.
- Browser
- Download file 880 MB
-
https://huggingface.co/splitner/spanclass-qa-dice-bionlp13cg/resolve/refs%2Fpr%2F1/optimizer.pt
- Command line
-
hf download hf://splitner/spanclass-qa-dice-bionlp13cg@refs/pr/1/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/splitner/spanclass-qa-dice-bionlp13cg/resolve/refs%2Fpr%2F1/optimizer.pt
880 MB
- Xet hash:
- ad936eea5a771212a7f583d1b4567662ce7a3d8a1852235818493f6d4897abee
- Size of remote file:
- 880 MB
- SHA256:
- eedbf08f938742afe5a40383d72a796a3b37d55487c5bdeaf00625847057f47e
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