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:
- d28d3012d83131bf57dcd802d256c8e75d265d6c19c5906ebcdf9b1723adea85
- Size of remote file:
- 1.12 GB
- SHA256:
- dddee087e9552cb6a8197efd9d86f3a69a48f3d5a35067661b9f5ceb90346c63
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