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:
- 327ba331ec03d53fcee19dad755cdf77984364df7347bf35a5a49cfb01b86891
- Size of remote file:
- 1.2 GB
- SHA256:
- 9b8273c302a413e4e0a77529f2fa533a3ae197de16417ac55dc4926374814078
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