Instructions to use junnyu/electra_small_generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use junnyu/electra_small_generator with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="junnyu/electra_small_generator")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("junnyu/electra_small_generator") model = AutoModelForMaskedLM.from_pretrained("junnyu/electra_small_generator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from junnyu/electra_small_generator: direct link, hf CLI and curl.
- Browser
- Download file 18.6 MB
-
https://huggingface.co/junnyu/electra_small_generator/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://junnyu/electra_small_generator/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/junnyu/electra_small_generator/resolve/main/pytorch_model.bin
18.6 MB
- Xet hash:
- bb647a5d7b7b53b22a9f47391c588c97f4f552442c607a00e8bc6cf7fe1e167f
- Size of remote file:
- 18.6 MB
- SHA256:
- 278b73bea290e2d4cc928febd5165ecc217ff682dd1acb050c09ce3ae053e015
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