Instructions to use Aleksandar/electra-srb-oscar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aleksandar/electra-srb-oscar with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Aleksandar/electra-srb-oscar")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Aleksandar/electra-srb-oscar") model = AutoModelForMaskedLM.from_pretrained("Aleksandar/electra-srb-oscar", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Aleksandar/electra-srb-oscar: direct link, hf CLI and curl.
- Browser
- Download file 2.67 kB
-
https://huggingface.co/Aleksandar/electra-srb-oscar/resolve/6e5480e10b7576cf9520ca64eba874a402da09a6/training_args.bin
- Command line
-
hf download hf://Aleksandar/electra-srb-oscar@6e5480e10b7576cf9520ca64eba874a402da09a6/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Aleksandar/electra-srb-oscar/resolve/6e5480e10b7576cf9520ca64eba874a402da09a6/training_args.bin
2.67 kB
- Xet hash:
- f9c0fb2accc951a8e80e0d69da2f2008c45344788a5e1b61fa0a94940312f353
- Size of remote file:
- 2.67 kB
- SHA256:
- 3b6dd877db0395eea93ec8c792e21da99fc0e893338d6cdc9d406a34101b4016
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