Instructions to use YakovElm/Qt10_ElectraModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YakovElm/Qt10_ElectraModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YakovElm/Qt10_ElectraModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YakovElm/Qt10_ElectraModel") model = AutoModelForSequenceClassification.from_pretrained("YakovElm/Qt10_ElectraModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from YakovElm/Qt10_ElectraModel: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/YakovElm/Qt10_ElectraModel/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://YakovElm/Qt10_ElectraModel/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/YakovElm/Qt10_ElectraModel/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 40d9c98d3823e855cd227689e20d57112f3f9e7cc499e7cae014009aef612008
- Size of remote file:
- 438 MB
- SHA256:
- 1e0ea7f855455829d8d53ce0b64a5e20d5cbd475211680d51ee80ab59702a8f3
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