Instructions to use YaHi/teacher_electra_small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YaHi/teacher_electra_small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YaHi/teacher_electra_small")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YaHi/teacher_electra_small") model = AutoModelForSequenceClassification.from_pretrained("YaHi/teacher_electra_small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from YaHi/teacher_electra_small: direct link, hf CLI and curl.
- Browser
- Download file 54.3 MB
-
https://huggingface.co/YaHi/teacher_electra_small/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://YaHi/teacher_electra_small/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/YaHi/teacher_electra_small/resolve/main/pytorch_model.bin
54.3 MB
- Xet hash:
- 6e1033513223debb98fb788a845b328eb57c41388e598d21af036661e8bc20e3
- Size of remote file:
- 54.3 MB
- SHA256:
- bd9215472073890038ab8f58f9c5729985894e63e7d206deee14b5af055011e7
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