Instructions to use YaHi/teacher_electra_small_building_binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YaHi/teacher_electra_small_building_binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YaHi/teacher_electra_small_building_binary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YaHi/teacher_electra_small_building_binary") model = AutoModelForSequenceClassification.from_pretrained("YaHi/teacher_electra_small_building_binary") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9df23d5db6a0392d749c953fbdfff6e3e614efb29ad747f299b79a1bbc238435
- Size of remote file:
- 54.3 MB
- SHA256:
- 75407204f6ad1436c245187e808223c2d7e6778259cfabba93793b1e4067f6af
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