Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use gerbejon/digilog-eform-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gerbejon/digilog-eform-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gerbejon/digilog-eform-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gerbejon/digilog-eform-classifier") model = AutoModelForSequenceClassification.from_pretrained("gerbejon/digilog-eform-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 19fc58261517b89dda201f6225811c88c2d77801d7a1a50a8e818cfba4e75cce
- Size of remote file:
- 1.08 GB
- SHA256:
- 340af5f79f889117dc258658bea11da0a16a37b40cf1aa3a50db69c57e1c9248
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.