Instructions to use splitner/single-qa-bionlp13cg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use splitner/single-qa-bionlp13cg with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("splitner/single-qa-bionlp13cg") model = AutoModel.from_pretrained("splitner/single-qa-bionlp13cg", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from splitner/single-qa-bionlp13cg: direct link, hf CLI and curl.
- Browser
- Download file 2.03 kB
-
https://huggingface.co/splitner/single-qa-bionlp13cg/resolve/main/training_args.bin
- Command line
-
hf download hf://splitner/single-qa-bionlp13cg/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/splitner/single-qa-bionlp13cg/resolve/main/training_args.bin
2.03 kB
- Xet hash:
- d642b57cfefc66c7b3bcd9c2302d48b9e075a7471c4669a6bcea404c704ee536
- Size of remote file:
- 2.03 kB
- SHA256:
- dccc28ee3c7a41bbda57a8c3e419ebf09c5290923d201e40953a5f443069c5a0
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