Instructions to use YakovElm/Apache15_ElectraModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YakovElm/Apache15_ElectraModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YakovElm/Apache15_ElectraModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YakovElm/Apache15_ElectraModel") model = AutoModelForSequenceClassification.from_pretrained("YakovElm/Apache15_ElectraModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from YakovElm/Apache15_ElectraModel: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/YakovElm/Apache15_ElectraModel/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://YakovElm/Apache15_ElectraModel/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/YakovElm/Apache15_ElectraModel/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- c7b3d20de2c47ee3a05b13b57f57f5ce45d1441e674290f1518e9c89d718a5fa
- Size of remote file:
- 438 MB
- SHA256:
- f62dd246691af358f5cc2a1253357cec2acfb8a842ed485a3e9756526abe990f
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