Instructions to use YakovElm/Qt5_ElectraModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YakovElm/Qt5_ElectraModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YakovElm/Qt5_ElectraModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YakovElm/Qt5_ElectraModel") model = AutoModelForSequenceClassification.from_pretrained("YakovElm/Qt5_ElectraModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from YakovElm/Qt5_ElectraModel: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/YakovElm/Qt5_ElectraModel/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://YakovElm/Qt5_ElectraModel/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/YakovElm/Qt5_ElectraModel/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 658bd103f433083aebfc740a3259cd720e265a28571bd22ed3b18408daabc4a6
- Size of remote file:
- 438 MB
- SHA256:
- 1214f8588beeca11cc15344169745a9a2310c5de6cd1059b50219d4516c43260
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