Instructions to use YakovElm/Apache20_ElectraModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YakovElm/Apache20_ElectraModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YakovElm/Apache20_ElectraModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YakovElm/Apache20_ElectraModel") model = AutoModelForSequenceClassification.from_pretrained("YakovElm/Apache20_ElectraModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from YakovElm/Apache20_ElectraModel: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/YakovElm/Apache20_ElectraModel/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://YakovElm/Apache20_ElectraModel/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/YakovElm/Apache20_ElectraModel/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 53142a993234cce0e372befc893167604053ae6169133dd00348da644e33514e
- Size of remote file:
- 438 MB
- SHA256:
- b0f18082ae37b254bff2fbe36c1dea614478723d3809da0d94d1e95074b3a294
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