Instructions to use kimsiun/ec_classfication_0502_google_electra_base_discriminator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kimsiun/ec_classfication_0502_google_electra_base_discriminator with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kimsiun/ec_classfication_0502_google_electra_base_discriminator")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kimsiun/ec_classfication_0502_google_electra_base_discriminator") model = AutoModelForSequenceClassification.from_pretrained("kimsiun/ec_classfication_0502_google_electra_base_discriminator") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e2988b25318ef9ba2a6181204bcc1f3217c4db8ac4581a70e4f675176918922c
- Size of remote file:
- 438 MB
- SHA256:
- 47134db071cea78e67bab6387e606c70759db56794efc1d24e04e8027d8dfcc8
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