Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
English
deberta-v2
Generated from Trainer
nlu
intent-classification
Eval Results (legacy)
text-embeddings-inference
Instructions to use cartesinus/mdeberta-v3-base_amazon-massive_intent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cartesinus/mdeberta-v3-base_amazon-massive_intent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cartesinus/mdeberta-v3-base_amazon-massive_intent")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cartesinus/mdeberta-v3-base_amazon-massive_intent") model = AutoModelForSequenceClassification.from_pretrained("cartesinus/mdeberta-v3-base_amazon-massive_intent") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c180b483542d60e60d0c60a3c9f7448202e1202b78eec14bbcc9d19e68c9391f
- Size of remote file:
- 1.12 GB
- SHA256:
- 8e11f4247bfe3c576931f7c125428c821ae5507a588a1ee7860f47394a3ad389
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