Text Classification
Transformers
Safetensors
modernbert
Generated from Trainer
text-embeddings-inference
Instructions to use Mathildeholst/classifier-clinc-MBbase-distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mathildeholst/classifier-clinc-MBbase-distilled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mathildeholst/classifier-clinc-MBbase-distilled")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mathildeholst/classifier-clinc-MBbase-distilled") model = AutoModelForSequenceClassification.from_pretrained("Mathildeholst/classifier-clinc-MBbase-distilled") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e4a5c2bed4434deb01759c4044a4cfcce5f4bf8cd95daec37b9fe83d80ea5996
- Size of remote file:
- 1.2 GB
- SHA256:
- b12ffbd4ee1fec35988c16dd75dd9e075e93f2f148f673ec0a859bca8866ecab
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