Instructions to use YakovElm/Apache5_ElectraModel_full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YakovElm/Apache5_ElectraModel_full with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YakovElm/Apache5_ElectraModel_full")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YakovElm/Apache5_ElectraModel_full") model = AutoModelForSequenceClassification.from_pretrained("YakovElm/Apache5_ElectraModel_full", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from YakovElm/Apache5_ElectraModel_full: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/YakovElm/Apache5_ElectraModel_full/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://YakovElm/Apache5_ElectraModel_full/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/YakovElm/Apache5_ElectraModel_full/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- f464a9bdf8360d50bce3c2c0b9a2a0ded823e72c0e263e9201fb1b89d555e1bb
- Size of remote file:
- 438 MB
- SHA256:
- 1403ac6aa39fe7d7179b70dc73f74640ca762bb6e894a987d1acc38a6b5ecd5c
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