Instructions to use google/electra-large-discriminator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/electra-large-discriminator with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("google/electra-large-discriminator") model = AutoModelForPreTraining.from_pretrained("google/electra-large-discriminator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/electra-large-discriminator: direct link, hf CLI and curl.
- Browser
- Download file 1.34 GB
-
https://huggingface.co/google/electra-large-discriminator/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://google/electra-large-discriminator/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/electra-large-discriminator/resolve/main/flax_model.msgpack
1.34 GB
- Xet hash:
- 4b5ea5047b16db53e198ddafbb20d708c048a8e399856bfebae513c8370dd366
- Size of remote file:
- 1.34 GB
- SHA256:
- ec1fdbae9e52d1977876a8088bba5587609aeee76261d44b28e289a430af14eb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.