Instructions to use google/electra-small-discriminator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/electra-small-discriminator with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("google/electra-small-discriminator") model = AutoModelForPreTraining.from_pretrained("google/electra-small-discriminator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/electra-small-discriminator: direct link, hf CLI and curl.
- Browser
- Download file 54.2 MB
-
https://huggingface.co/google/electra-small-discriminator/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://google/electra-small-discriminator/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/electra-small-discriminator/resolve/main/flax_model.msgpack
54.2 MB
- Xet hash:
- 8d15514ee4f1739ca0e9100b45e8f5dd050b7aa94a66f0ec53030dc9207a84f2
- Size of remote file:
- 54.2 MB
- SHA256:
- 732fbc87c683a6d2430ee2060068c2eba2b2ee286dabd8acc5921d192f055970
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.